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Solid-state hydrogen storage technology has emerged as a disruptive solution to the "last mile" challenge in large-scale hydrogen energy applications, garnering significant global research attention. This paper systematically reviews the Chinese research progress in solid-state hydrogen storage material systems, thermodynamic mechanisms, and system integration. It also quantitatively assesses the market potential of solid-state hydrogen storage across four major application scenarios: on-board hydrogen storage, hydrogen refueling stations, backup power supplies, and power grid peak shaving. Furthermore, it analyzes the bottlenecks and challenges in industrialization related to key materials, testing standards, and innovation platforms. While acknowledging that the cost and performance of solid-state hydrogen storage are not yet fully competitive, the paper highlights its unique advantages of high safety, energy density, and potentially lower costs, showing promise in new energy vehicles and distributed energy fields. Breakthroughs in new hydrogen storage materials like magnesium-based and vanadium-based materials, coupled with improved standards, specifications, and innovation mechanisms, are expected to propel solid-state hydrogen storage into a mainstream technology within 10–15 years, with a market scale exceeding USD 14.3 billion. To accelerate the leapfrog development of China's solid-state hydrogen storage industry, increased investment in basic research, focused efforts on key core technologies, and streamlining the industry chain from materials to systems are recommended. This includes addressing challenges in passenger vehicles, commercial vehicles, and hydrogen refueling stations, and building a collaborative innovation ecosystem involving government, industry, academia, research, finance, and intermediary entities to support the achievement of carbon peak and neutrality goals and foster a clean, low-carbon, safe, and efficient modern energy system. [ABSTRACT FROM AUTHOR]

As lithium‐ion batteries are the main power source of new energy vehicles, making accurate predictions of unknown State of Charge (SOC) during vehicle operation for vehicle data monitoring is vital to the advancement of intelligent new energy vehicles. In this manuscript, an expression tree‐based genetic programming regression model (ETGPR) is proposed to estimate the real‐time SOC of lithium‐ion batteries. The proposed model mainly adopts the symbolic regression technique. In addition to the current–voltage curves being fed into the model, an additional approach is designed to ensure real‐time model predictions in dynamic situations, which includes the previous moment's power in the input parameters. Different seed hyperparameters in the model are set, and the model automatically performs evolutionary calculations. Subsequently, each parameter of the model is optimally adjusted to obtain a set of regression expressions that accurately reflect the relationship between the SOC and each parameter after a specified number of iterations. Finally, the generated expression is proven to perform better in terms of its ability to capture the nonlinear relationship between SOC and battery variables. Also, the model demonstrates excellent robustness in the presence of notable noise from input‐independent features compared to other models, a root mean square error (RMSE) of less than 0.3% and a mean absolute error (MAE) of less than 0.2% are achieved. Furthermore, the potential of the model's implement‐ability under variable temperature and real driving data conditions is verified. [ABSTRACT FROM AUTHOR]

Based on the work of air conditioners for new powerful cars, the author created a heat pump air conditioner with various functions, such as cooling and heating passengers, cooling and preheating the battery, defogging, defrosting, and PTC heating. Developed basic components of AC heat pumps such as scroll compressor model, running condenser model, combined evaporator model, plate evaporator extended valve model, and radial basis function neural network model for predicting compressor volumetric efficiency and isentropic efficiency. The accuracy of the gas-flow, gas-flow, and plate evaporator simulation model was verified. The maximum error between the experimental and simulated values of compressor power, heat exchanger, and system COP in various operating models is 0.34~10.09, which is consistent with the experimental results. correct and can be used for ventilation pump research. Also, an operational simulation analysis platform was used to analyze the performance of the heat pump and study the system characteristics. It is clear that this system provides more warmth to the occupants in the defrost mode, and current research on the operation of the air conditioning pump is based on the first law of thermodynamics. [ABSTRACT FROM AUTHOR]

Within the increasingly complex and changeable market environment of new energy vehicles, consumers' attention to product safety has increased significantly, and higher, updated requirements are put forward at the level of product safety. Simultaneously, a product harm crisis, which often entails product recalls, can lead to consumer concerns regarding product specifications and security. Based on the heuristic-systematic model, this study verified the effect of information processing on the vehicle purchase intention of consumers during crisis situations and conducted an empirical study through questionnaires and structural equation modelling. The data obtained in this study presents the following relationships: (1) risk perception has a significant and positive influence on information search and systematic processing but a negative influence on heuristic processing; (2) heuristic processing and systematic processing have a significant and positive influence on purchase intention; (3) information search has a significant and positive influence on heuristic processing and systematic processing. The study can offer a relevant basis and suggestions for risk communication of new energy vehicle enterprises, thereby fundamentally improving consumer loyalty. [ABSTRACT FROM AUTHOR]

Battery safety issue is a key factor that hindered the reuse of retired batteries on new energy vehicles, while charge state, voltage and temperature are important parameters to judge the safety state of batteries. Based on this, a joint fault diagnosis of battery based on real vehicle data was proposed. Firstly, the data was obtained from the real vehicle data platform, and the feature extraction was carried out by data preprocessing and dung beetle optimizes K-nearest neighbor ( DPO-KNN) algorithm. Then, the extracted features were input into the established autoregressive integrated moving average model, autoregressive integrated moving average model (ARIMA) fault diagnosis model to realize real-time diagnosis and accurate location for low and overvoltage of battery cells. Finally, voltage, state of charge ( SOC) and temperature were combined to determine whether there was a risk of triggering thermal runaway, and different alarm levels were issued according to the degree of danger. It can not only accurately locate the abnormal position of the monomer, but also alarm 9 s in advance, effectively preventing the risk of thermal runaway of the battery. It achieved a good effect in engineering practical application, and lied a foundation for the future step recycling of power batteries and the research and development of safety warning platform. [ABSTRACT FROM AUTHOR]

With the intensification of energy and environmental crises, new energy vehicles have become a beacon of hope. The performance of their core component, the power battery system, is directly related to the vehicle's range and safety. The heat generation of power batteries during operation is particularly critical, as temperatures that are too high or too low can adversely affect battery performance. Therefore, optimizing the Battery Thermal Management System (BTMS) is of paramount importance. However, existing research has largely focused on system design and experimental validation, while the thermodynamic analysis of battery heat generation mechanisms and the study of performance adaptability under complex conditions remain insufficient. This study aims to delve into the thermodynamic behavior of power batteries by establishing models for their heat generation and dissipation, thereby optimizing the design of the BTMS to enhance the overall performance and safety of the system. Initially, a thermodynamic model of the battery pack under various conditions was constructed. Based on this, existing thermal management technologies were evaluated and optimized, leading to the proposal of viable optimization solutions. The outcomes of this study contribute to improving the energy efficiency and safety levels of new energy vehicle power batteries, holding significant practical and theoretical value for the advancement of the new energy vehicle industry. [ABSTRACT FROM AUTHOR]

In the face of some product harm crises of new energy vehicles, which are difficult to find out the real reasons, it is highly significant for new energy vehicle companies to choose appropriate communication strategies. This study examines the impact of three communication tactics on consumer trust and purchase willingness using two rounds of scenario simulation experiments based on stimulus–organism–response theory. The results show that, when compared with deny and rebuild method, the diminish strategy is the most effective in reducing the influence of ambiguous product harm crises on consumer behaviours. Simultaneously, brand reputation has a moderating effect. For new energy vehicle companies with high brand reputation, the communication effect of diminish strategy is the best. Only a higher‐cost rebuild strategy can be viable for automotive businesses with a poor brand reputation. Thus, when dealing with ambiguous product harm crises, new energy vehicle companies should focus on efficient and low‐cost diminish strategy. Meanwhile, to take the initiative in dealing with an ambiguous product harm crisis, we must improve the technical maturity of products as well as improve the after‐sales service system to continuously enhance the brand reputation. [ABSTRACT FROM AUTHOR]

In order to ensure good charging performance of new energy vehicles, the charging station was designed and the relevant oscillation circuits were optimized. The function and structure of the charging station was determined, and through a hierarchical framework, not only the success rate factor could be corrected, but also a resonant converter was combined to achieve efficient charging over a wide battery voltage range. The linear charging management chip was adopted, which integrated high-precision constant voltage source, temperature monitoring, charging status display, and battery charging completion termination function. The changes in excitation current and switching frequency during the charging process were studied, and the optimization basis for the relevant circuits was determined. A trigger was added to the input end of the oscillator to filter the input signal, which improved the accuracy of the RC oscillator cycle. The clock reference oscillation circuit and stable voltage power supply circuit were optimized. In order to verify the effectiveness of the proposed electronic control design, a hardware platform for the test of DC output characteristics was built. The results indicate that the output voltage waveform can effectively meet the working requirements. [ABSTRACT FROM AUTHOR]

The development of new energy vehicles has become a common choice for countries worldwide to reduce greenhouse gas emissions and improve the global ecological environment, with China being no exception. However, challenges, such as finding charging stations, accessing residential areas, and highway charging, have hindered the green and high-quality growth of the new energy vehicle industry. This study, set against the backdrop of China's 2018 policy to gradually redirect local purchase subsidy funds for new energy vehicles towards supporting the construction and operation of charging infrastructure, utilizes panel data from 282 prefecture-level cities from 2016 to 2021. A difference-in-differences model is constructed to compare the impact of infrastructure development on carbon emissions before and after the policy's implementation. The study finds that policy has a negative effect on carbon emissions, especially in the second and third year after the policy's implementation. Even after controlling for variables such as residents' wealth levels, population size, environmental pollution, energy consumption, and government support, the results remain significant. Heterogeneity analysis reveals that the effect of the promotion of charging infrastructure on carbon emissions is greater in southern and central parts of China. [ABSTRACT FROM AUTHOR]

Low-carbon and environmentally friendly living boosted the market demand for new energy vehicles and promoted the development of the new energy vehicle industry. Accurate demand forecasting can provide an important decision-making basis for new energy vehicle enterprises, which is beneficial to the development of new energy vehicles. From the perspective of an intelligent supply chain, this study explored the demand forecasting of new energy vehicles, and proposed an innovative SARIMA-LSTM-BP combination model for prediction modeling. The data showed that the RMSE, MSE, and MAE values of the SARIMA-LSTM-BP combination model were 2.757, 7.603, and, 1.912, respectively, all of which are lower values than those of the single models. This study therefore, indicated that, compared with traditional econometric forecasting models and deep learning forecasting models, such as the random forest, support vector regression (SVR), long short-term memory (LSTM), and back propagation neural network (BP) models, the SARIMA-LSTM-BP combination model performed outstandingly with higher accuracy and better forecasting performance. [ABSTRACT FROM AUTHOR]

Under the global consensus of carbon peaking and carbon neutrality, new energy vehicles have gradually become mainstream, driven by the dual crises regarding the atmospheric environment and energy security. When choosing new energy vehicles, consumers prefer to browse the post-purchase reviews and star ratings of various new energy vehicles on platforms. However, it is easy for consumers to become lost in the high-star text reviews and mismatched reviews. To solve the above two issues, this study selected nine new energy vehicles and used a multi-attribute decision making method to rank the vehicles. We first designed adjustment rules based on star ratings and text reviews to cope with the issue of high star ratings but negative text reviews. Secondly, we classified consumers and recommended the optimal alternative for each type of consumer to deal with the issue of mismatched demands between review writers and viewers. Finally, this study compared the ranking results with the sales charts of the past year to verify the feasibility of the proposed method initially. The feasibility and stability of the proposed method were further verified through comparative and sensitivity analyses. [ABSTRACT FROM AUTHOR]

To study the electromagnetic compatibility of energy vehicles, the conducted electromagnetic interference (EMI) prediction model of a motor drive system under no-load state is established. The occurrence of EMI in each component of an electric vehicle is discussed along with some mitigation techniques. Further, an EMI filter topology using an LC filter is demonstrated, and the procedure has been verified in two switching power supply control applications. The simulation value of the differential mode interference voltage prediction model is essentially the same as the measured value in the transmitted interference frequency band. Except for a few frequency points, the error is small in most frequency bands, which is about 15%. The values of common mode current simulation and the measured values of the predicted model are essentially the same in the frequency range studied, and the error is about 8% within the allowable range. The horizontal and vertical components of the 10-m electric field on the right side of the car body were modeled in the high-frequency structure simulator program and compared with the results measured in a half-wave anecogenic chamber. The electric field amplitude is basically consistent and can reach approximately 80%, which confirms the accuracy of the vehicle radiation EMI simulation hypothesis. [ABSTRACT FROM AUTHOR]

In order to ensure the stability of battery management power system, improve the reliability of on-board electronic products, and ensure the stability of thermal energy recovery power system, the author proposes an electromagnetic compatibility optimization scheme based on wiring harness, power module, and PCB noise, taking the battery management system of vehicle electronic components as an example, the role of electromagnetic compatibility on products is described, the hardware circuit is analyzed and designed by electromagnetic compatibility design theory to ensure the reliability of vehicle components. The electromagnetic stability of the power battery is guaranteed through the electromagnetic compatibility optimization analysis of the battery management system, so as to achieve more stable battery management. The experimental results show that each module of the battery management system works stably, and the disturbance degree test shows that the resonant noise of the battery management system disappears, and there is no obvious narrowband electromagnetic disturbance, and the overall value is below the limit of 20 dB. In conclusion the electomagnetic compatibility optimization scheme can effectively ensure the stability of the battery management power system, and indirectly ensure the stability of the heat recovery power system. [ABSTRACT FROM AUTHOR]

With the gradual promotion and popularization of new energy vehicles, the safety of new energy vehicles has attracted more and more attention. The thermal management system (TMS) is the key to whether the key assembly of new energy can work normally. In this paper an optimized control method is developed for the intelligent control of the TMS with the lowest overall energy consumption by taking into account the performance requirements of each subsystem. To realize this, the simulation of the integrated TMS is carried out along with a real vehicle test platform to provide practical and feasible solutions. This study has improved the design depth and level of system intelligence and digitalization. [ABSTRACT FROM AUTHOR]

In order to ensure the stability of battery management power system, improve the reliability of on-board electronic products, and ensure the stability of thermal energy recovery power system, the author proposes an electromagnetic compatibility optimization scheme based on wiring harness, power module, and PCB noise, taking the battery management system of vehicle electronic components as an example, the role of electromagnetic compatibility on products is described, the hardware circuit is analyzed and designed by electromagnetic compatibility design theory to ensure the reliability of vehicle components. The electromagnetic stability of the power battery is guaranteed through the electromagnetic compatibility optimization analysis of the battery management system, so as to achieve more stable battery management. The experimental results show that each module of the battery management system works stably, and the disturbance degree test shows that the resonant noise of the battery management system disappears, and there is no obvious narrowband electromagnetic disturbance, and the overall value is below the limit of 20 dB. In conclusion the electomagnetic compatibility optimization scheme can effectively ensure the stability of the battery management power system, and indirectly ensure the stability of the heat recovery power system. [ABSTRACT FROM AUTHOR]

Air pollution is a major obstacle to future sustainability, and traffic pollution has become a large drag on the sustainable developments of future metropolises. Here, combined with the large volume of real-time monitoring data, we propose a deep learning model, iDeepAir, to predict surface-level PM 2.5 concentration in Shanghai megacity and link with MEIC emission inventory creatively to decipher urban traffic impacts on air quality. Our model exhibits high-fidelity in reproducing pollutant concentrations and reduces the MAE from 25.355 µg/m3 to 12.283 µg/m3 compared with other models. And identifies the ranking of major factors, local meteorological conditions have become a nonnegligible factor. Layer-wise relevance propagation (LRP) is used here to enhance the interpretability of the model and we visualize and analyze the reasons for the different correlation between traffic density and PM 2.5 concentration in various regions of Shanghai. Meanwhile, As the strict and effective industrial emission reduction measurements implementing in China, the contribution of urban traffic to PM 2.5 formation calculated by combining MEIC emission inventory and LRP is gradually increasing from 18.03% in 2011 to 24.37% in 2017 in Shanghai, and the impact of traffic emissions would be ever-prominent in 2030 according to our prediction. We also infer that the promotion of vehicular electrification would achieve further alleviation of PM 2.5 about 8.45% by 2030 gradually. These insights are of great significance to provide the decision-making basis for accurate and high-efficient traffic management and urban pollution control, and eventually benefit people's lives and high-quality sustainable developments of cities. [Display omitted] [ABSTRACT FROM AUTHOR]

In view of the current new energy vehicles only implement torque control on the drive motor, resulting in the engine speed fluctuation, affecting the vehicle running stability and reducing the engine efficiency and energy saving effect, a new energy vehicle engine speed control method based on Internet of vehicles technology is proposed. The battery and operation data are obtained through the sensor of the new energy vehicle Internet of vehicles, and the data are controlled and transmitted by the controller area network. The overall external dynamic characteristics of the engine are analyzed by using the average value model. According to the principle of engine dynamic system, the throttle intake manifold model, combustion torque model and power output sub model are constructed respectively. The speed is controlled by double working points According to the variable parameter PID control of the engine, the load prediction is introduced to optimize the speed control, and the internal pressure value of the accumulator is obtained through the SOP value to realize the speed control of the new energy vehicle engine. The experimental results show that the engine speed control method can effectively improve the energy-saving effect and efficiency of the engine, reduce the engine speed fluctuation, and improve the vehicle running stability under the condition of meeting the driver's torque demand. [ABSTRACT FROM AUTHOR]

In order to cope with increasingly severe environmental problems, the development of new energy vehicles has been strongly supported. The rapid development of new energy vehicles has led to the development of power batteries. It is vital to choose the appropriate new energy vehicle battery which is the power source of the new energy vehicles. This paper proposes a new model based on D numbers, which combines the Best-worst method (BWM) and Evaluation based on Distance from Average Solution (EDAS) method. First, in order to express the uncertainty of expert decision-making, this paper uses D number to describe the evaluation information. Then the D-BWM model is applied to determine the weight of the given criteria. Next, the D-EDAS model is constructed for the selection of new energy vehicle battery suppliers. The results show that this newly proposed model is reasonable. Finally, the validity and robustness of the model in this paper are demonstrated through sensitivity analysis. [ABSTRACT FROM AUTHOR]

Traditional charging stations have a single function, which usually does not consider the construction of energy storage facilities, and it is difficult to promote the consumption of new energy. With the gradual increase in the number of new energy vehicles (NEVs), to give full play to the complementary advantages of source-load resources and provide safe, efficient, and economical energy supply services, this paper proposes the optimal operation strategy of a PV-charging-hydrogenation composite energy station (CES) that considers demand response (DR). Firstly, the operation mode of the CES is analyzed, and the CES model, including a photovoltaic power generation system, fuel cell, hydrogen production, hydrogen storage, hydrogenation, and charging, is established. The purpose is to provide energy supply services for electric vehicles (EVs) and hydrogen fuel cell vehicles (HFCVs) at the same time. Secondly, according to the travel law of EVs and HFCVs, the distribution of charging demand and hydrogenation demand at different periods of the day is simulated by the Monte Carlo method. On this basis, the following two demand response models are established: charging load demand response based on the price elasticity matrix and interruptible load demand response based on incentives. Finally, a multi-objective optimal operation model considering DR is proposed to minimize the comprehensive operating cost and load fluctuation of CES, and the maximum–minimum method and analytic hierarchy process (AHP) are used to transform this into a linearly weighted single-objective function, which is solved via an improved moth–flame optimization algorithm (IMFO). Through the simulation examples, operation results in four different scenarios are obtained. Compared with a situation not considering DR, the operation strategy proposed in this paper can reduce the comprehensive operation cost of CES by CNY 1051.5 and reduce the load fluctuation by 17.8%, which verifies the effectiveness of the proposed model. In addition, the impact of solar radiation and energy recharge demand changes on operations was also studied, and the resulting data show that CES operations were more sensitive to energy recharge demand changes. [ABSTRACT FROM AUTHOR]

This study aims to investigate the impact of dual credit policy on the diffusion of new energy vehicles (NEVs) from the perspective of complex interactions among heterogeneous manufacturers. Thus, the market competition and credit cooperation relationships, constituting the complex interrelated system in NEV diffusion, are considered in this paper. To this end, we established a double-layer complex network to depict the asymmetric competition and cooperation structure, and developed an evolution game model on network, revealing the diffusion rule and trend of NEVs among manufacturers. Simulation results show that the existence of credit cooperation relationship can effectively improve the diffusion of NEVs, especially when implementing cooperative strategy that prioritizes helping manufacturers with low sale profits. Such a cooperative strategy is effective for maintaining high diffusion of NEVs even under low NEV credit's trading price. Meanwhile, the monopoly competitive structure characterized by scale free is harmful to NEV diffusion. However, credit cooperation can eliminate the by-effect of monopoly structure greatly by adopting the strategy of distributing by sale profits. In addition, manufacturers are advised to learn from their competitors during the evolutionary process, which should be the focus of manufacturers to maximize the NEV diffusion under small world competitive structure. [ABSTRACT FROM AUTHOR]

New energy power battery has a high current during fast charging and discharging, producing a huge amount of heat. The rational operation of the battery thermal management system (BTMS) plays an important role in increasing the energy storage capacity and service life of the power battery. This paper explores the battery thermal management and health state assessment of new energy vehicles. For the power battery of new energy vehicles, the fast charging is very likely to cause overheating. By analyzing this phenomenon, we derived a comprehensive control strategy for the charging and discharging of power battery, which optimizes the battery thermal management. Then, the main controlling factors were collaboratively controlled for the thermal management during the fast charging of the power battery of new energy vehicles, and the collaborative control standards and energy consumption laws of the system were discussed in details. After that, the backpropagation neural network (BPNN) was combined with adaptive genetic algorithm (AGA) to establish a nonlinear model between the health state indices and battery capacity of the power battery of new energy vehicles, and the model was applied to estimate the health state of the battery. Finally, the effectiveness of the proposed model was proved through experiments. [ABSTRACT FROM AUTHOR]

After dividing China's new energy vehicle (NEV) pilot promotion cities into license plate- and non-license plate-restricted cities, the choice of experiment and latent class model were used in this study to classify the consumers in the two kinds of cities from the technical, economical, and convenience dimensions. Then the differences in consumers' product attribute preferences and willingness to pay (WTP) for NEVs in different cities and different types were compared and the impact of consumers' socioeconomic features was analyzed. The results showed that the traffic preference type is the major consumer class in Chinese license plate-restricted cities with the highest overall WTP, followed by the subsidy dependence consumers with the lowest overall WTP and finally the mileage preference consumers with the overall WTP in the middle. In the non-license plate-restricted cities, mileage preference type is the largest consumer class with the highest overall WTP. Similarly, the subsequent type is the subsidy dependence consumers with the lowest overall WTP. And finally the smallest type is the infrastructure preference consumers with the overall WTP in the middle. Further analysis revealed that in the license plate-restricted cities, consumers' WTP for the product attributes of NEVs in the convenience and technical dimensions goes far beyond than that in the non-license plate-restricted cities, with higher WTP for road use rights and driving range attributes, while consumers in the non-license plate-restricted cities prefer attributes in the economic dimensions with higher WTP for subsidy intensity attribute. [ABSTRACT FROM AUTHOR]

New energy vehicles (NEV) have become an important driving force for carbon reduction in the transportation industry. This paper adopts the extended environmental pressure assessment (STIRPAT) model and the time-varying difference in differences (DID) model to evaluate the effectiveness of the NEV subsidy policy to achieve sustainable governance. The results show that the NEV subsidy policy can significantly decrease the carbon emission of the transport industry. The mechanism analysis results indicate that the NEV subsidy policy can decrease carbon emissions by promoting a green transformation of the consumer car purchasing structure. Further analysis found that a "fraudulent subsidy" can significantly weaken the policy effect of subsidies. The results of heterogeneity analysis indicate that the subsidy policies introduced by different levels of government have different effects. The subsidy policy of the central government has a more significant effect, and repeated subsidies from central and local governments will weaken the policy's effectiveness. These findings provide valuable insights for policymakers in developing countries to optimize subsidies for new energy vehicles in reducing carbon emissions in the transportation industry. • We explore the impact of the NEV subsidy policy on carbon emissions of the urban transport industry in Chinese cities. • The NEV subsidy policy significantly reduces the carbon emissions of the urban transport industry. • The NEV subsidy policy can promote a green transformation of the consumer car purchasing structure. • The fraud of government subsidies will weaken the carbon reduction effect of the NEV subsidy policy. • The impact of NEV subsidy policy from central and local governments on urban carbon reduction may vary. [ABSTRACT FROM AUTHOR]

Brake wear particles (BWPs) are considered one of the most significant non-exhaust particle emission sources from motor vehicles. Previous studies have primarily focused on BWPs from conventional fuel vehicles (CFVs), with limited research available on BWPs from new energy vehicles (NEVs). We developed an independent BWP emission testing system applicable to NEVs and conducted BWP emission tests on representative NEVs and CFVs under various testing cycles via a chassis dynamometer. The BWP emission characteristics of the NEVs equipped with regenerative braking system significantly differed from those of gasoline vehicles. For transient emission characteristics, gasoline vehicles exhibited higher peak concentrations during brake events than brake drag events, while those with regenerative braking exhibited the opposite feature. Under continuous braking, the concentration of ultrafine particles emitted by NEVs was reduced by more than 3 orders of magnitude compared to gasoline vehicles. In terms of single-particle morphology, BWPs could be mainly divided into three categories: carbonaceous particles, iron-rich particles, and mixed metal particles. We obtained realistic emission characteristics of BWPs from NEVs, which could provide data support and a scientific basis for the formulation of relevant emission standards and control measures in the future. [Display omitted] • We develop and establish an independent brake wear particle emission testing system. • The brake wear particles from new energy vehicles significantly differ from gasoline vehicles. • New energy vehicles exhibit higher peak concentrations during brake drag than actual braking. • Carbonaceous particles, iron-rich particles and mixed metal particles were the three categories. [ABSTRACT FROM AUTHOR]

The current top-down method for calculating carbon emissions in the building sector erroneously includes carbon emissions from charging new energy vehicles (NEVs). This error is particularly concerning as the number of NEVs is expected to rise significantly in the future, thereby exacerbating the negative impact on the formulation of effective carbon reduction policies. This study analyzes carbon emissions in Beijing's building sector from 2011 to 2020 and estimates NEV-related indirect emissions from 2015 to 2020. Findings show that electricity consumption is the primary energy source in Beijing's building sector, increasing electricity-related carbon emissions from 63.36 % to 67.18 % of the total. Additionally, the indirect carbon emissions from NEVs have exhibited a steady increase from 208,800 tons in 2015 to 1.18 million tons in 2020, with their contribution to the overall carbon emissions from buildings escalating from 0.27 % to 1.44 %. Intriguingly, the study uncovers that private new energy cars do not significantly differ from conventional private fuel passenger cars in terms of their indirect carbon emissions. The findings of this study are expected to inform the development of accurate carbon emission estimation strategies in Beijing's building sector and facilitate the formulation of effective policies in the future. • Energy consumption of charging NEVs deducted from the building sector. • Carbon emission factors of electricity and heat in Beijing were reported. • Urban residential building has the greatest carbon emission reduction potential. • Energy use intensity is crucial for carbon reduction in residential buildings. [ABSTRACT FROM AUTHOR]

The sales of new energy vehicles (NEVs) and the construction of charging infrastructure promote and constrain each other. It is crucial for the development of the new energy vehicle industry to understand the gap clearly and accurately between the supply and demand of NEV charging infrastructure. In this paper, a neural network combined model based on convolutional neural network (CNN) and long and short-term memory (LSTM) is introduced for accurate prediction of NEVS sales and charging infrastructure ownership. Compared with other traditional and combined models, the CNN-LSTM combined model performs best in multiple evaluation metrics while using less computing power. The RMSE, MAE, MAPE, and R2 of the CNN-LSTM combined model were 52.80, 42.67, 17 %, and 0.78, respectively. Accordingly, it is sufficient to demonstrate the excellent prediction performance of the CNN-LSTM combined model constructed in this paper. The forecast results show that in 2025, the ratio of NEVs to public charging piles will rise to 10.2:1 and the ratio to private charging piles will fall to 2.5:1. The overall ratio shows a downward trend and is expected to reach 2:1. There is a gap in the demand for NEV charging infrastructure. Finally, this paper makes suggestions for narrowing the gap between the supply and demand of NEV charging infrastructure and the sustainable development of the NEV industry. [ABSTRACT FROM AUTHOR]

With resource shortage and environmental pollution becoming more and more serious, the development of new energy vehicles (NEVs) plays an important role. In this paper, the hybrid method of best-worst method (BWM), Multi-Objective Optimization by Ratio Analysis plus Full Multiplicative Form (MULTIMOORA), and Evaluation based on Distance from Average Solution (EDAS) is used to evaluate new energy vehicles (NEVs) and select the best new energy vehicle. BWM method is used to obtain the subjective preference weight, MULTIMOORA method is used to integrate the objective data with the subjective weight to evaluate new energy vehicles, and the final ranking of alternatives is obtained by the EDAS method. The paper collect the data of 22 representative new energy vehicle types in China, the validity and feasibility of the method is verified. [ABSTRACT FROM AUTHOR]

Aiming at the coexistence of fuel vehicles and new energy vehicles in the current market, to explore the long-term diffusion of new energy vehicles under the competitive situation, firstly, this paper summarized the key variables influencing the customer adoption rate, and constructed the long-term new energy vehicles diffusion system dynamics model, which based on interspecific competition mechanism and customer perceived utility. Then, it considered the impact on the new energy vehicles diffusion of customer fuzzy perception, and used a fuzzy control system to deal with new energy vehicles adoption rate. Finally, it was simulated according to the current market data under Vensim PLE. The results show that, under the situation of customer fuzzy perception, the new energy vehicles' market scale will be equal to fuel vehicles around 2052, and then replace fuel vehicles gradually. Besides, the effect of new energy vehicles price fluctuation on customer adoption rate, which is opposite to that of charging facilities. [ABSTRACT FROM AUTHOR]

With the reduction of government subsidies for new energy vehicle, it has become an important decision problem for traditional vehicle enterprises with new energy vehicle production qualification to decide how much proportion of new energy vehicles should be produced. By maximizing the utility of the vehicle enterprise, this study analyses the influence of enterprise’s production decision and consumer’s preference payment premium for the performance of new energy vehicle on optimal mixed production and pricing decision after the subsidies withdraw from the new energy vehicle market. The Results show that: (1) consumer’s payment premium increases the proportion of new energy vehicles produced by automobile enterprise. The enterprise only produces traditional fuel vehicles instead of new energy vehicles, when the premium is less than a certain level; and when the payment premium is higher than a certain threshold, the enterprise merely produces new energy vehicles instead of traditional ones. (2) As the rise of consumer’s payment premium, the amount of people who consume vehicles show a downward trend, and finally only 1/2 of consumers will remain to purchase automobiles. (3) There shows a U-shaped relationship between the optimal profit of vehicle enterprise and consumer payment premium that the profit of vehicle enterprise will decline first and then rise with the increase of consumer payment premium. [ABSTRACT FROM AUTHOR]

Regulatory policy is an important factor affecting the development of emerging ride-hailing platforms. However, there is little research exploring the impact of specific regulatory policies on platforms from the perspective of enterprise growth. Taking the Chinese ride-hailing platform (RHP) as an example, this study employs the system dynamics method to simulate and analyze the impact of restrictive policies on the model of vehicles and the qualification of drivers on the growth of RHP. Furthermore, it compares and evaluates the effects of different countermeasures taken by the platform in the face of policy uncertainty. Specifically, this study dynamically examines the growth of platforms under loose/strict policy and short/long term policy scenarios, and evaluates the coping strategy of self-built fleet adopted by platform. The results show that regulatory policy uncertainty brings great challenges to the overall development of the RHP. A Self-built fleet not only has the potential to improve RHP's ability to resist policy risks but also increases the platform's scale effect at both ends of supply and demand. It is worth noting that RHP should devise the most suitable strategy according to a comprehensive evaluation of the characteristics of the regulatory policies and the cost-effectiveness of the countermeasure. It also shows that the promotion and application of new energy vehicles and automated vehicles can bring good profit margins to RHP in the future. This study can help policymakers and managers better understand of the impact of regulatory policy on the growth of RHP and also provide a valuable reference for promoting the healthy and orderly development of ride-hailing market. [ABSTRACT FROM AUTHOR]

COVID-19 threatens human life and health, and affects travel frequency and travel mode choice. Clarifying the main drivers of the purchase intention of new energy vehicles (NEVs) under the epidemic is important for formulating phasing policy regarding the promotion of green mobility and the construction of smart cities. Based on this, this study introduces variables such as perceived risk and trust under the epidemic, aiming to investigate the main drivers of the purchase intention of NEVs in China under epidemic through an extended technology acceptance model. The data covered the public in urban, suburban, and rural areas of China (n = 884) and were analyzed using structural equation model. Specifically, trust had a significant positive effect after the epidemic. Perceived risk did not directly affect the public's intention to purchase new energy vehicles, but had an indirect effect through attitude and perceived utility, attitude and trust, and social interaction and trust. In addition, the significant positive impacts of subsidy and non-subsidy incentive are further validated, which reinforces the current view. Considering the limited literature related to the purchase intention of NEVs under the epidemic in developing countries, it is hoped that these findings will provide new perspectives for future research, and provide guidance for phasing policy formulation. [ABSTRACT FROM AUTHOR]

Urban transportation problems, primarily characterized by traffic congestion and exhaust emissions, continue to worsen, significantly impeding the economic and social development of cities. Road pricing strategies have emerged as an effective approach to tackle urban transportation problems, and their successful implementation in numerous cities have garnered significant attention. In this context, this study introduces a collaborative road pricing strategy tailored for mixed traffic flow comprising both conventional vehicles (CVs) and new energy vehicles (NEVs). CVs and NEVs are considered as two distinct types of cars with heterogeneous characteristics. The collaborative road pricing strategy consists of two components: congestion pricing and emission pricing. A bi-level programming model for the collaborative road pricing strategy is built. Exhaust emissions within the low-emission zone (LEZ) are used as constraints for the model, while the optimization objective of the model involves minimizing the sum of total travel time and total emissions of the road network. The viability of the proposed collaborative road pricing scheme is demonstrated through numerical tests within the second ring road in Beijing, China. The results imply that the service level of the road network can be improved by implementing the collaborative road pricing scheme. It also concludes that, increasing the penetration of new energy vehicles would help to decrease traffic congestion and emissions. [Display omitted] • A collaborative road pricing scheme for heterogenous vehicles is formulated. • Heterogenous vehicles include conventional vehicles and new energy vehicles (NEVs). • The low-emission zone (LEZ) is districted as the emission constraint in the scheme. • The influence of the NEV penetration and the LEZ emission constraint is examined. • The penetration of NEVs would help to decrease traffic congestion and emissions. [ABSTRACT FROM AUTHOR]

This study explores the impact of the behavioral strategies of manufacturers, consumers, recyclers, and the government on carbon emissions reduction in the whole life cycle of new energy vehicles (NEVs) in China by establishing a quadrilateral evolutionary game model. It analyzes the influence of relevant factors on the carbon emissions of NEVs and ranks them accordingly. The study identifies low-carbon production by manufacturers, green product purchases by consumers, self-built recycling systems by recyclers, and production subsidies by the government as the future direction for the development of NEVs. Promotion strategies are proposed for carbon emission reduction of NEVs. The research results indicate that consumers' preference for low-carbon products can benefit manufacturers, and their green consumption behavior will not change until consumer subsidies reach a certain level. The government can implement consumer subsidy policies to increase consumers' motivation for green purchasing. Production subsidies can alleviate the transformation pressure of manufacturers towards low-carbon production, allowing them to focus on important factors such as opportunity costs and market benefits. The strategy choices of recyclers are influenced by dismantling costs and recycling profits. Furthermore, when the profitability of low-carbon production for manufacturers is guaranteed, they are more willing to take responsibility for recycling waste NEVs. The government has different benefits in the process of production and consumer subsidies, and its subsidy strategy choices are also influenced by the decisions of manufacturers and consumers. This makes the government to implement a dynamic subsidy system based on the producer responsibility system. [Display omitted] • The quadratic evolutionary game model of the whole life cycle carbon emission of new energy vehicles is established. • The factors affecting the carbon emission of new energy vehicles are ranked. • The future development direction of new energy vehicles is prospected. • The promotion strategies of new energy vehicles carbon emission reduction are proposed. [ABSTRACT FROM AUTHOR]

There are still key technological bottlenecks in new energy vehicle (NEV). It is necessary to achieve key technological breakthroughs through interaction of various elements in innovation ecosystem. We constructed an innovation ecosystem with subject and environment elements as antecedent variables, and data comes from the city statistical yearbook and statistical bulletin. We constructed the comprehensive index of key technology innovation performance, and data comes from Incopat global patent database. We analyzed the sample of 62 listed NEV enterprises from 2011 to 2020 by fuzzy-set qualitative comparative analysis (fsQCA) and necessary condition analysis (NCA). The results show that: (1) The key technological breakthrough in NEV requires interaction of multiple elements, and single element does not constitute a necessary condition; (2) The configuration of breakthrough path evolves dynamically, from infrastructure-government dual driven, to economy-service dual driven, then to technology-government dual driven, and last to technology-consumer dual driven; (3) The key elements' necessary degrees measured by bottleneck level change dynamically. This study improves theoretical value of key technology bottleneck breakthrough based on innovation ecosystem, and provides practical value for enterprises and governments to improve effective coordinate relationship with multiple elements interaction in innovation ecosystem. [ABSTRACT FROM AUTHOR]

With the new round of scientific and technological revolution and industrial change accelerating, "electrification, intelligence, network and sharing" has become a new trend of the current automotive industry reform. Accelerating the cultivation and development of new energy vehicles has not only become an urgent task to effectively alleviate the pressure of energy and environment in China and promote the sustainable development of the automobile industry, but also a strategic measure to accelerate the transformation and upgrading of the automobile industry in China. In view of the low survival rate of high-tech innovating enterprises and high input and high risk of high-tech enterprises, it is of great significance to assess and evaluate the operating efficiency of the high-tech innovating enterprises. This study used the entropy weight method to establish a DEA -based business performance evaluation index model to evaluate and analyze the business performance of the listed new energy vehicles enterprises in China in 2018. The result shows that most of the new energy vehicles enterprises are in the state of increasing returns to scale, conforming to the characteristic of high growth of high-tech enterprises; however, the overall operational efficiency of these enterprises is very low and some of them face the problem of obvious scientific research input redundancy; therefore, the improper input-output framework is the main reason lead to the low scale efficiency for the enterprises and provide corresponding policy proposals for these problems. [ABSTRACT FROM AUTHOR]

China's new energy vehicle (NEV) industry, which survives with powerful policy intervention and fostering, is an important branch of Chinese green energy policy revolution against climate change and circumstance issues. In the study, the roadmap of China's policy exploration on developing China's NEV industry within the time window of 2001–2020 was investigated systematically. Powerful policy intervention plays an important role in initializing the framework of China's NEV industry under the comprehensive situation when China's innovation capability and automobile technology were both at unsatisfactory state. China's policy of developing NEV market demonstrates that intense government intervention is necessary and successful at the starting stage of the NEV industry. Delicate balance between governmental intervention and market self-adjustment should be intensified by suitable policies. The pilot innovations and the serious lessons of China's policy explorations are of both practical and research significance for other developing countries. • China's policy development of new energy vehicle industry is schemed thoroughly. • Intense government intervention is necessary and successful at the starting stage. • China's new energy vehicle industry is a government-centralized dance. • Delicate balance between policy intervention and market-adjustment should be kept. [ABSTRACT FROM AUTHOR]

At present, the low carrying capacity of the charging cable and the long charging time has become an important factor restricting the promotion of new energy vehicles. It is necessary to put forward higher requirements for the cable heat dissipation technology to further increase the carrying capacity. The rapid heat dissipation of low-voltage charging cable becomes a technical problem that needs to be solved urgently. The application researches of forced cooling technology, phase-change technology and insulating layer modification material technology in enhancing heat dissipation of cable are reviewed in this paper according to the heat dissipation demand of low-voltage cable. The realization methods and advantages and disadvantages of these research directions are pointed out. The main development direction of the study on the enhancing heat dissipation of low-voltage charging cable is described. [ABSTRACT FROM AUTHOR]

By incorporating socio-culture elements into cognitive behavior models, this study explored the influence of supportive policy and customer perceived value on customer purchase intentions of new energy vehicles, and probed the mediating effects of the frugality and the concept of "mianzi". In the current study, the construction of customer perceived value was divided into three dimensions: price factor, functional quality, and service quality. Based on 406 samples in the survey, the study applied structural equation modeling to test the hypotheses. The results showed that supportive policy not only directly influenced price factor and purchase intentions, but also had an indirect positive impact on customer purchase intentions through the mediating effect of the frugality. Meanwhile, three dimensions of customer perceived value had different influences on the purchase intentions. Price factor only affected customer purchase intentions directly, and functional quality only exerted indirectly positive effect through the mediating effect of the frugality on customer purchase intentions. Service quality significantly promoted the concept of "mianzi", while the concept of "mianzi" had no significant effect on customer purchase intentions of new energy vehicles. [ABSTRACT FROM AUTHOR]

Unlike many Western countries, the Chinese state has a much more active role in innovation that includes direct involvement with actors in innovation processes and the use of state capacity, money, and power to attain certain goals. With the rise of China, innovation processes that critically depend on state action, often labeled state‐led innovation, have thus received growing scholarly attention. However, only few contributions study the specific sector of new energy vehicles (NEV) and policy measures applied at the city level. This paper examines policy and planning tools used in Shenzhen, China, to assert innovation in the NEV industry, using an evaluation of documents and interviews. The paper finds that a city can play a decisive role in the implementation of innovation policy, and Chinese cities in particular make use of a broad set of innovation support measures ranging from binding quotas, public procurement, and incentives to bans and orders. The findings underline the importance of strong regulatory instruments that do not conform to the Western notion of market‐compliant policy, but nevertheless work effectively in the Chinese context. Moreover, the results highlight how successful policy support for innovation in the NEV can be implemented. [ABSTRACT FROM AUTHOR]

The mass diffusion of new energy vehicles (NEVs) in the automobile market depends largely on consumers' acceptance behavior. In China, traditional culture induces attitudinal ambivalence in consumers' purchase intention of NEVs. This study investigated the role of attitudinal ambivalence on consumers' purchase intentions. An extended technology acceptance model (TAM) that incorporates attitudinal ambivalence is proposed. We conduct two sub-studies to verify the reliability of the proposed model by measuring subjective and objective attitudinal ambivalence respectively. The empirical results demonstrated that perceived usefulness, perceived ease of use, and perceived risk have a significant impact on the purchase intention of NEVs through the partial mediation of attitudinal ambivalence. Perceived risk and perceived ease of use have the strongest stimulating effect on attitudinal ambivalence and purchase intention respectively. Finally, we provide several managerial and policy implications for the advancement of NEVs. [ABSTRACT FROM AUTHOR]

In recent years, with the changes in the international energy situation, new energy vehicles (NEVs) have become an essential choice for people to travel. The center control touch screen (CCTS) of NEVs is an important part of the user's interaction with the vehicle, which is quite different from a conventional fuel vehicle. Therefore, it is necessary to conduct research on the CCTS of NVEs. This study integrates multiple research methods to investigate the visual imagery and user preferences for CCTSs in NEVs. The results of the study show that the horizontal version with small rounded angles without a border is the optimal design solution for the visual imagery dimension, whereas the vertical version with large rounded angles and a border is the worst design solution in terms of the visual imagery dimension. The design without a border can increase users' preference and purchase intention to a certain extent. The results of the above study can effectively reflect the potential user demand for NEVs' CCTSs, which also has positive implications for enhancing the overall user experience of NEVs. [ABSTRACT FROM AUTHOR]

This paper examines how the state can facilitate the establishment of a domestic production network in new energy vehicles (NEVs), from the making of electric vehicle batteries and battery management systems to the manufacturing of NEVs. The case of China illustrates how a non-firm actor was able to create the largest NEV market in the world by implementing proactive policies for market creation and new industrial regulations for cost and range parity. To facilitate the further development of domestic production networks for NEVs, the Chinese government shifted its regulatory parameters and leveraged the market size to drive the incumbent global automakers to rejig their product portfolios and form joint ventures with domestic NEV-makers in China. This provides a prima facie case illustrating how a proactive state can take a dominant role in establishing a domestic production network without coupling with global lead firms in global production networks. [ABSTRACT FROM AUTHOR]

Highlights • A SD model was established based on the competitive Lotka-Volterra model. • New energy vehicles will occupy the dominant position in China around 2050. • China's strategic planning target in 2020 can hardly be achieved. • Policy support and market maximum capacity have separate decisive impact. Abstract New energy vehicles (NEVs) development has recently become China's national strategy. For NEVs, the scientific prediction of market scale is the guarantee to formulate the effective policy planning. Considering the competition and substitution phenomenon between traditional fuel vehicles (TFVs) and NEVs, we propose a system dynamics (SD) model to investigate and predict the market evolution of NEVs and TFVs in China based on the competitive Lotka-Volterra (LV) model. Furthermore, the effect mechanism of key model parameters is evaluated by sensitivity analysis. Finally, the potential environmental impacts of NEVs in China are analyzed based on the above simulation results. It shows that NEVs will continue to grow rapidly in the coming decades and will dominate in Chinese vehicle market around 2050. Government subsidies and other consumption stimulus factors are the main driving force for NEVs development in its early stages, however, along with the policy stimulus and policy influence gradually weakening, growth in later stages will rely on convenience factors and cost advantages brought by technological progress and infrastructure improvements. It is noteworthy that the national strategic planning target in 2020 can hardly be achieved under China's current policy system and market conditions. The results of sensitivity analysis reveal that the policy support and maximum market capacity show different decisive influences on the development trend of the entire automotive market. In addition, if China's relevant energy and environmental planning can be effectively implemented, the rapid expansion of NEVs will significantly reduce the environmental impact of vehicles. [ABSTRACT FROM AUTHOR]

Highlights • Subjective norms plays an important role in purchasing intentions. • There is an “awareness-behavior gap” whereby low-carbon awareness has a moderating effect on behavior via psychological factors. • Low-carbon subjective knowledge and low-carbon objective knowledge have different influencing mechanism on purchasing intention. • Acceptability of policies has positive impact on adoption of New Energy Vehicles. Abstract This paper investigates the salience of social-psychological factors in explaining why drivers purchase (or fail to purchase) New Energy Vehicles (NEVs)—including hybrid electric vehicles, battery electric vehicles, and fuel cell electric vehicles—in China. A questionnaire measuring six dimensions (including attitudes, subjective norms, perceived behavioral control, personal norms, low-carbon awareness and policy) was distributed in Tianjin, where aggressive policy incentives for NEVs exist yet adoption rates remain low. Correlation analysis and hierarchical multiple regression analyses are applied data collected through 811 valid questionnaires. We present three main findings. First, there is an “awareness-behavior gap” whereby low-carbon awareness has a slight moderating effect on purchasing behavior via psychological factors. Second, subjective norms has a stronger influence on intention to purchase New Energy Vehicles than other social-psychological factors. Third, acceptability of government policies has positive significant impact on adoption of New Energy Vehicles, which can provide reference potential template for other countries whose market for New Energy Vehicles is also in an early stage. [ABSTRACT FROM AUTHOR]

To cope with the environmental pollution caused by carbon emissions, Western countries, such as Switzerland and Germany, have implemented corporate carbon taxes to reduce carbon emissions and have achieved significant results. As one of the world's most carbon-intensive countries, China must take serious action to limit future emission increases through the implementation of carbon tax policies. This study investigated the evolutionary strategies and mechanisms of the interaction between new energy vehicle manufacturers and local governments under static and dynamic carbon taxes. Based on prospect theory, we constructed evolutionary game models between new energy vehicle manufacturers and local governments under static and dynamic carbon tax mechanisms. This study explored the impact of different initial values on the evolutionary results of the game and the different evolutionary paths of the system under static and dynamic carbon tax mechanisms. The ideal carbon tax starting rate was determined to be 0.15. The results of the theoretical model analysis were simulated to provide a theoretical reference for the establishment of a carbon tax system conducive to low-carbon development. The results of the study were: (1) there were differences in the paths and outcomes of the system's evolution to a stable state under different initial values and combinations of strategies; (2) the dynamic carbon tax mechanism was more favorable for the development of the new energy vehicle industry, and the system had no stable point and equilibrium strategy under the static carbon tax mechanism; and (3) the use of a lower starting rate at the beginning of the carbon tax collection process was helpful in encouraging new energy vehicle firms to select a low-carbon production strategy. • This study incorporates prospect theory into evolutionary game analysis, minimizing parameter subjectivity in model and benefit simulations. • The low-carbon strategies of both sides of the game under static and dynamic carbon tax mechanisms are studied. • This study determined the best initial carbon tax rate based on study parameters and found that a lower initial carbon tax rate is optimal for the development of the new energy vehicle industry. [ABSTRACT FROM AUTHOR]

The dual-credit policy is expected to achieve subsidy policy withdrawal through the effective market-oriented mechanism of credit trading, which has both rewards and sanctions for auto firms. The policy can activate the endogenous motivation of automakers to conserve energy and cut carbon emissions, which aids in creating a long-term mechanism to foster the growth of the auto industry. This paper examines the impact of the dual-credit policy on the quantity and quality of green innovation in auto firms using the difference-in-differences (DID) model. Based on the data of listed firms in the auto industry in the China A-share market from 2014 to 2020, we discover that the DCP-assessed auto firms' green innovation performance improves significantly after implementing the DCP. By analyzing the mediating effect, we identify that the dual-credit policy enhances corporate environmental responsibility and R&D investment, thus improves their green innovation performance. Further, the role of the dual-credit policy in enhancing green innovation increases significantly with the weakening of government environmental subsidies and the strengthening of government environmental penalties. Our findings expand the research on the implementation effects of the dual-credit policy and policies combining environmental regulation and market incentives. We emphasize the importance of the dual-credit policy in furthering the reform of the energy consumption structure and building a green innovation system that is focused on the market, and we propose that the government play a complementary role with the market through reasonable regulation and supervision. • The dual-credit policy (DCP) can improve auto firms' green innovation. • The corporate environmental responsibility and R&D investment are primary mechanisms for improvement of green innovation. • Government subsidies dampens the green innovation-enhancing effect of the DCP. • Government environmental penalties promotes the green innovation-enhancing effect of the DCP. [ABSTRACT FROM AUTHOR]

Public attitudes and sentiments are considered important factors driving the development of new energy vehicles (NEVs) in China, yet few studies have effectively articulated the public attitudes and sentiments on a national scale. Social media platforms provide open and large-scale data on how the public views NEVs. Accordingly, based on data collected from Sina Weibo, the largest open social media platform in China, this study adopts web crawler and text mining to explore public attitudes and sentiments toward NEVs. The results show that the majority of NEVs followers belong to the media and broadcasting unit, which may lead to exaggerated advertising of NEVs performance. Public pay more attention to NEVs in environmental pollution and developed economies regions than others. In addition, it is found that the public is generally concerned about driving range, policies, battery charging and safety performance, and NEVs-related attributes. Some interesting findings are that preferential policies such as unrestricted driving are more popular with the public than tax incentives, and the public attaches a high degree of importance to the brand in the attributes of NEVs. Moreover, the Chinese public has relatively positive sentiments on NEVs, mainly due to the impact of China's carbon reduction targets. Negative sentiments are mainly due to safety and battery technology issues. Finally, some policy implications derived from the discussion are given. [Display omitted] • A national attitude survey on new energy vehicles (NEVs) is conducted using Weibo data. • Driving range, policy, battery technology and NEVs-related attributes are the four hot topics. • Chinese public sentiment towards NEVs is relatively positive. [ABSTRACT FROM AUTHOR]

New energy vehicles (NEVs) have become an effective way to solve environmental pollution and energy shortages in transportation. Therefore, China has issued Regulations on Average Fuel Consumption and New Energy Vehicle Credits for Passenger Vehicle Enterprises(dual credit policy), to promote the development of NEVs. This paper establishes a technological innovation decision-making model under the conditions of information asymmetry and information sharing. This model obtains the optimal solution for NEV technology innovation considering the market demand prediction of the manufacturer and supplier. Moreover, this paper provides the conditions for information sharing of demand forecasting for the manufacturer and supplier and designs the incentive mechanism for information sharing. The results show that the dual credit policy positively stimulates the technological innovation of NEVs, but information asymmetry negatively affects the dual credit policy's incentive effect. The supplier is always willing to share information; however, whether the manufacturer shares information depends on the supplier's technology innovation cost coefficient. In addition, implementing the dual credit policy enhances the manufacturer's and supplier's willingness to share information; the higher the credit coefficient of technological innovation and the credit price is, the stronger the manufacturer and supplier's willingness to share information. • Dual credit policy can effectively stimulate to increase NEVs' technology innovation. • Dual credit policy enhances both parties' willingness to share information. • Higher credit price & technology innovation credit coefficient, policy affect more. • Information asymmetry negatively affects the dual credit policy's incentive effect. • Supplier is willing to share information, but manufacturer needs certain conditions. [ABSTRACT FROM AUTHOR]