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The torsional vibration of the shaft system in hybrid car engines has a significant impact on the overall performance of the vehicle, and it is more complex in hybrid cars compared to traditional cars. Traditional methods for torsional vibration analysis of shaft systems have significant limitations and cannot handle nonlinear and transient problems. To explore the torsional vibration characteristics of hybrid vehicle shaft systems, a simplified engine shaft system torsional vibration equivalent model is innovatively constructed. In addition, a method for quickly determining the confidence level of the torsional vibration equivalent model is proposed. Additionally, the transient dynamic characteristics of a multi-body dynamics model containing a dual mass flywheel are analyzed in depth using the time-domain solver of AVL-exact PU. The results demonstrated that the simulation of 4th and 6th harmonics resonated at critical speeds of 4,195 rpm and 2,771 rpm, respectively, with angular displacement amplitudes of 0.141 deg and 0.047 deg. In fact, resonance was measured at 4,250 rpm and 3,040 rpm, with amplitudes of 0.14 deg and 0.052 deg. These two were basically consistent in key parameters. When the shaft model was started under operating conditions, the amplitudes of harmonics 1, 2, and 4 were basically consistent below 750 rpm, and there were slight differences after 750 rpm. Therefore, the AVL-based engine torsional vibration simulation model constructed has high credibility. [ABSTRACT FROM AUTHOR]

AbstractAs an energy-efficient transportation innovation, hybrid vehicles (HVs) have the potential to minimize carbon emissions and address environmental issues. The study is novel as it presents significant theoretical contributions within the theory of planned behavior (TPB) framework. Firstly, it integrates the perceived seriousness of environmental problems as a predictor, enhancing understanding of individual responses to environmental concerns. Secondly, it expands the TPB model by introducing willingness to pay for HVs as a moderator, acknowledging the economic aspect of adopting environmentally friendly technologies. These additions enrich the TPB framework, offering insights into the interplay between psychological determinants and economic considerations in behavior change. The study therefore aims to extend the TPB by incorporating two key elements: perceived seriousness of environmental issues and willingness to pay for HVs. We find that perceived seriousness of problems in the environmental has positive impact on attitude toward adoption of HVs, subjective norms, perceived behavioral control, intentions to adopt and actual use of HVs. TPB constructs have positive impact on intentions to adopt and actually use HVs. Moreover, intentions to adopt HVs also positively influence the actual use of HVs. Moreover, the results show that the serial mediations are also in play, whereby perceived seriousness of environmental issues influences TPB constructs, which influence intentions to adopt HV which in turn influence the actual use of HVs. We also find that willing to pay for HVs plays an enhancing role as a moderator in the TPB model. [ABSTRACT FROM AUTHOR]

In recent years, the adoption of alternative fuels and hybrid vehicles has necessitated radical changes to meet the energy needs of the automotive sector. Hybrid electric vehicles are used as a perfect step between traditional fossil fueled internal combustion engines and fully electric vehicles. Deeply related to this, complicated industry and manufacturers need simulation programs to reduce both the cost of test sets and to use time with the highest efficiency. Before the production, especially in automotive sector, the simulation and prototyping procedure is playing an indispensable role. For this study, the AVL-Cruise simulation tool was chosen. Due to its capability to keep up with evolving technological structures, this program can be easily implemented in hybrid vehicle simulations. In this study, a hybrid engine model was created based on a 1.5 L, four-cylinder gasoline engine and a 10 kW electric motor. Energy analysis, based on the variations in the CVT and AMT transmissions of a hybrid motor, was conducted under three different driving cycles and compared in detail. Additionally, energetic balance like exergy is executed for this model. Sankey diagrams were employed to illustrate the differences and energy consumptions of the vehicle based on the selected modeling criteria. As a result, the CVT is slightly better behaviors than AMT both fuel consumption (2.5–4%), emission reducing (1.5–4.6%) and energetic balances (3.6–5%). • Hybrid vehicles energy analyses are determined with Sankey diagrams. • Effects of CVT and AMT transmission to HEVs energetic outputs were compared. • Effects of various driving cycles on HEV components were discussed detailed. • CVT is slightly better than AMT with reducing the fuel consumption and emissions. • For this study, CVT is more energetic efficiency with 5% improvement vs AMT. [ABSTRACT FROM AUTHOR]

Increasingly stringent pollutant emission regulations and a customer demand for a high-fuel economy drive the modern automotive industry to hurriedly solve the problem of decarbonization and powertrain efficiency, leading R&D towards alternative powertrain solutions and fuels. Electrification, today, plays the biggest role in the topic, with Mild Hybrid Electrified Vehicles (MHEVs) being the most cost-effective architectures, displaying dominance in smaller markets such as Brazil. One of the biggest challenges for HEVs' development is the complexity of the hybrid control system, knowing when to actuate the electric machine, and the optimum power delivery, plus the gearshift schedule becomes a hard optimization problem that plays a key role in powertrain efficiency and cost savings for the customer. This paper proposes the implementation of a genetic algorithm (GA) as a machine learning-based control strategy to determine the torque split and the gear engaged for each driving condition of an MHEV operation, aiming to optimize fuel consumption. A quasi-static model of the vehicle was developed in Matlab/Simulink version 2022b, the virtual vehicle was then tested following the FTP75 and HWFET driving cycles. Simulation results indicate that the control decisions taken by the GA are qualitatively coherent for all operation conditions, and even quantitatively coherent in some cases, and that the software has the potential to be used as a control strategy outside the simulation environment, in future steps of development. [ABSTRACT FROM AUTHOR]

Using a unique panel dataset on air pollution and car sales from thirty major cities in China across three years, we estimate the impact of air pollution on the adoption of hybrid and electric vehicles. To identify the causal effect, we use three sets of interactive fixed effects to control for a large group of potential confounders and an instrument for the air pollution variable. Our results show that worse air quality leads consumers to purchase more hybrid and electric cars, and the effect is larger in cities with higher incomes. These findings are consistent with predictions from the social preferences theory and point out new directions for strategies to promote the adoption of hybrid and electric cars. [ABSTRACT FROM AUTHOR]

In the era of rapid technological advancement and evolving industrial landscapes, embracing the concept of the factory of the future (FoF) is crucial for companies seeking to optimize efficiency, enhance productivity, and stay sustainable. This case study explores the concept of the FoF and its role in driving the energy transition and digital transformation within the automotive sector. By embracing advancements in technology and innovation, these factories aim to establish a smart, sustainable, inclusive, and resilient growth framework. The shift towards hybrid and electric vehicles necessitates significant adjustments in vehicle components and production processes. To achieve this, the adoption of lighter materials becomes imperative, and new technologies such as additive manufacturing (AM) and artificial intelligence (AI) are being adopted, facilitating enhanced efficiency and innovation within the factory environment. An important aspect of this paradigm involves the development and utilization of a modular, affordable, safe human–robot interaction and highly performant intelligent robot. The introduction of this intelligent robot aims to foster a higher degree of automation and efficiency through collaborative human–robot environments on the factory floor and production lines, specifically tailored to the automotive sector. By combining the strengths of human and robotic capabilities, the future factory aims to revolutionize manufacturing processes, ultimately driving the automotive industry towards a more sustainable and technologically advanced future. This study explores the implementation of automation and the initial strides toward transitioning from Industry 4.0 to 5.0, focusing on three recognized, large, and automotive companies operating in the north of Portugal. [ABSTRACT FROM AUTHOR]

Copyright of Environmental & Social Management Journal / Revista de Gestão Social e Ambiental is the property of Environmental & Social Management Journal and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This review analyzed the literature data about the global warming potential (GWP) of the lithium-ion battery (LIB) lifecycle, e.g., raw material mining, production, use, and end of life. The literature data were associated with three macro-areas—Asia, Europe, and the USA—considering common LIBs (nickel manganese cobalt (NMC) and lithium iron phosphate (LFP)). The GWP (kgCO2eq/kg) values were higher for use compared to raw material mining, production, and end of life management for hydrometallurgy or pyrometallurgy. Considering the significant values associated with the use phase and the frequent application of secondary data, this study also calculated the GWP of LIBs applied in public urban buses in Turin, Italy. The 2021 fleet (53% diesel, 36% natural gas, and 11% electric buses) was compared to scenarios with increasing shares of hybrid/electric. The largest reduction in CO2eq emissions (−41%) corresponded to a fleet with 64% electric buses. In conclusion, this review highlighted the bottlenecks of the existing literature on the GWP of the LIB lifecycle, a lack of data for specific macro-areas for production and use, and the key role of public transportation in decarbonizing urban areas. [ABSTRACT FROM AUTHOR]

The study utilizes open-access data to generate power demand curves for a hybrid automotive system, testing twelve configurations with three different energy management strategies and four values for the degree of hybridization (DOH), the latter representing the share of the total power of the vehicle powertrain supplied by the battery. The first control logic (Battery Main—BTM) uses mainly batteries to satisfy the power demand and fuel cells as backup, while in the other two controllers, fuel cells operate continuously (Fuel Cell Main—FCM) or within a fixed range (Fuel Cell Fixed—FCF) using batteries as backup. The results are assessed in terms of H2 consumption, overall system efficiency, and fuel cell predicted lifespan. The battery is heavily stressed in the BTM and FCF logics, while the FCM logic uses the battery only occasionally to cover load peaks. This is reflected in the battery's State of Charge (SOC), indicating different battery stress levels between the BTM and FCF modes. The FCF logic has higher stress levels due to load demand, reducing battery lifetime. In the BTM and FCM modes, the fuel cell operates with variable power, while in the FCF mode, the fuel cell operates in a range between 90 and 105% of its rated power to ensure its lifetime. In the BTM and FCM modes, hydrogen consumption decreases at almost the same rate as the DOH increases, due to a decrease in battery capacity and a smaller amount of hydrogen being used to recharge it. In contrast, the FCF control logic results in a larger fuel consumption when the DOH decreases. In terms of FC durability, the FCF control logic performs better, with a predicted lifetime ranging from 1815 h for DOH = 0.5 to 2428 h for DOH = 0.1. The FCM logic has the worst performance, with a predicted lifetime of 800 to 808 h, being almost insensitive to the DOH variation. Simulations were performed on two different driving cycles, and similar trends were observed. Simulations taking into account fuel cell (FC) performance degradation showed an increase in hydrogen consumption of approximately 38% after 12 years. Overall, this study highlights the importance of optimizing control systems to improve the performance of fuel cell hybrid vehicles, also taking into account the component of performance degradation. [ABSTRACT FROM AUTHOR]

Copyright of Computer Measurement & Control is the property of Magazine Agency of Computer Measurement & Control and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Considering the potential warming potential and long lifetime of nitrous oxide (N2O) as a greenhouse gas, exploring its emission characteristics is of great significance for its control and the achievement of sustainable development goals. As vehicles are a significant source of N2O emissions, in this study we conducted a detailed investigation of N2O in the exhaust of light-duty vehicles using a chassis dynamometer. We selected one conventional gasoline vehicle and two hybrid electric vehicles. We found that the N2O emissions from all the tested vehicles complied with the China 6 emission regulation, with emission factors of 7.7 mg/km, 6.8 mg/km, and 17.1 mg/km, respectively, for the three vehicles. Driving conditions played a crucial role in N2O emissions, with emissions generated primarily during extra-high-speed conditions, possibly due to the higher driving speed and greater number of acceleration/deceleration events. Furthermore, while hybrid electric vehicles emitted less NOx compared to conventional gasoline vehicles, their N2O emissions were closely tied to their engine operating conditions. Surprisingly, we discovered that hybrid electric vehicles emitted more N2O during frequent engine start–stop cycles, which could be related to the mechanisms of N2O generation. These findings contribute to a better understanding of the N2O emission characteristics of vehicles and will inform the development of emission control strategies to better promote global sustainable development.

Nowadays, the most energy efficient are electric and hybrid vehicles. Despite the very high cost and insufficient design perfection, they are replacing traditional cars with internal combustion engines. In hybrid vehicles, it is relatively easy to implement energy storage systems using reversible electric machines and electric batteries. The results of a study on electrical energy generation in a vehicle are presented. The methods of mathematical and simulation modelling were used. The efficiency of operation of a vehicle with an electrical energy recovery unit is shown. The data of the generated electric current in the form of the received voltage when the vehicle is moving on various types of road surfaces are given. As a result of simulation modelling, it was found that one recuperator can generate an average of about 3 V, 12 V can be obtained from all four installed recuperators, which is enough to charge the storage units of the hybrid power plant.

The significant contribution of the transportation sector to carbon dioxide emissions (CO2e) has become a developing concern for legislators and environmental experts. Innovation in hybrid electric vehicle-related technologies (IHVRTs) has been identified as a possible strategy for reducing CO2e in the transportation industry. Even though IHVRTs have the potential to reduce CO2e, there are insufficient studies on their impact in the top three Asian knowledge-based economies (Japan, South Korea, and Japan). This study attempts to address this gap in the literature by investigating the association between innovation in IHVRTs and CO2e in the top three Asian knowledge-based economies, with independent variables gross domestic product per capita (GDPPC), economic complexity (ECC), renewable energy consumption (RNEC), and financial development (FD). The model's coefficients are estimated using the augmented mean group, which considers cross-country dependencies and country-specific effects. The empirical findings indicate that IHVRTs have a substantial negative effect on CO2e. In addition, FD has a favorable relationship with CO2e, whereas ECC has a negative relationship with CO2e. The results also demonstrated that RNEC reduces CO2e, whereas the GDPPC reduces CO2e. The policy implications of the results imply an urgent need for additional investment in IHVRTs and a transition towards more environmentally conscious and less ecologically damaging economic activity. [ABSTRACT FROM AUTHOR]

In the past few years, it can be seen that the automotive market has been developing quite rapidly, especially when it comes to electric cars. This is because the development of sustainable cars seems to be an extremely important issue at the moment. Nowadays, cars with different propulsion systems (among others electric, hybrid, gas, or hydrogen) can be met on the roads. But, political action is mainly aimed at electric cars. Such an approach will certainly lead to fundamental changes in production processes in the near future via the emergence and development of new technologies in the field of electric passenger cars. Therefore, the manuscript discusses the concept of vehicles with different types of power supply, with the main emphasis on electric vehicles. The essence of electric vehicles, their genesis, rationale for development, and growth are indicated. The different markets around the world, through the prism of, on the one hand, programs supporting the purchase and use of this type of vehicle and, on the other hand, factors limiting and inhibiting their uptake, are also discussed. The research was conducted in a group of both current and potential drivers from Eastern Poland, with different categories of grouping variables used in the analyses. On the basis of the research carried out and the results obtained, it can be argued that due to various factors, the respondents' opinions are varied, and there are no unambiguous conclusions stating that such solutions will soon be available. Indeed, a number of doubts and barriers were noted among respondents. Driver preferences are therefore a key issue, but production capacity and the profitability of investments in the purchase of vehicles with an electric power supply should also be taken into account. [ABSTRACT FROM AUTHOR]

The thermal management of the batteries in electrical and hybrid vehicles is a major concern for operation safety, battery life, and performance. In the current research, the temperature of the battery is tracked for 10,000 s of operation while using a Ranque–Hilsch vortex tube (RHVT) for the thermal management of the battery. An analytical model is developed and validated to study the impact of the heat generated per unit volume from the battery, the mass ratio for the cold air at the outlet to the total air at the inlet (x), entered air pressure, temperature, and mass flow rate. The peak temperature of the battery can be reduced by increasing the pressure and mass flow rate of the air at the inlet, decreasing the temperature of the air at the inlet, and using four RHVTs instead of a single RHVT. The proposed system significantly decreased the maximum temperature of the battery to 48.12 °C, compared to the battery thermal management method of using direct air, which resulted in a temperature of 75.73 °C. Furthermore, employing four RHVTs to cool the battery further reduced the maximum temperature from 48.12 to 11.23 °C, demonstrating a substantial improvement compared to utilizing a single RHVT. Utilizing the RHVT provides a good solution for the battery thermal management problem because it is cheap, small, and reduces the temperature of the air rapidly. [ABSTRACT FROM AUTHOR]

Copyright of Przegląd Elektrotechniczny is the property of Przeglad Elektrotechniczny and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In the present study, an attempt was made to simulate the hybrid self-power generation process from a diesel engine and propose sustainable power-share management for this self-power hybrid electrical-diesel platform from the viewpoints of environmental and economic aspects (life cycle perspective). This concept means that when the engine works at part-load condition, we need to bring the engine operating conditions to optimal load, and along with doing the necessary work, in parallel, the rest of the power be used to generate electricity to be stored in the battery for more consumption in addition to reducing pollution and reducing fuel consumption by moving towards sustainable energy production. This case study examines the differences between using a diesel engine at idle and maximum load conditions when less engine power is required and if using a diesel engine in a diesel-electricity hybrid cycle. According to the obtained results, it can be concluded that to achieve the most negligible environmental impact, a lower share of generating power can be allocated to electricity generation in higher cycles than the share of generating electrical power in lower cycles. In other words, by increasing the engine speed, the amount of power consumption used to generate electricity relative to the power required from the diesel engine should be reduced so that the system suffers the most negligible environmental impact.

Increasingly stringent pollutant emission regulations and a customer demand for a high-fuel economy drive the modern automotive industry to hurriedly solve the problem of decarbonization and powertrain efficiency, leading R&D towards alternative powertrain solutions and fuels. Electrification, today, plays the biggest role in the topic, with Mild Hybrid Electrified Vehicles (MHEVs) being the most cost-effective architectures, displaying dominance in smaller markets such as Brazil. One of the biggest challenges for HEVs’ development is the complexity of the hybrid control system, knowing when to actuate the electric machine, and the optimum power delivery, plus the gearshift schedule becomes a hard optimization problem that plays a key role in powertrain efficiency and cost savings for the customer. This paper proposes the implementation of a genetic algorithm (GA) as a machine learning-based control strategy to determine the torque split and the gear engaged for each driving condition of an MHEV operation, aiming to optimize fuel consumption. A quasi-static model of the vehicle was developed in Matlab/Simulink version 2022b, the virtual vehicle was then tested following the FTP75 and HWFET driving cycles. Simulation results indicate that the control decisions taken by the GA are qualitatively coherent for all operation conditions, and even quantitatively coherent in some cases, and that the software has the potential to be used as a control strategy outside the simulation environment, in future steps of development.

This review analyzed the literature data about the global warming potential (GWP) of the lithium-ion battery (LIB) lifecycle, e.g., raw material mining, production, use, and end of life. The literature data were associated with three macro-areas—Asia, Europe, and the USA—considering common LIBs (nickel manganese cobalt (NMC) and lithium iron phosphate (LFP)). The GWP (kgCO2eq/kg) values were higher for use compared to raw material mining, production, and end of life management for hydrometallurgy or pyrometallurgy. Considering the significant values associated with the use phase and the frequent application of secondary data, this study also calculated the GWP of LIBs applied in public urban buses in Turin, Italy. The 2021 fleet (53% diesel, 36% natural gas, and 11% electric buses) was compared to scenarios with increasing shares of hybrid/electric. The largest reduction in CO2eq emissions (−41%) corresponded to a fleet with 64% electric buses. In conclusion, this review highlighted the bottlenecks of the existing literature on the GWP of the LIB lifecycle, a lack of data for specific macro-areas for production and use, and the key role of public transportation in decarbonizing urban areas.

The study utilizes open-access data to generate power demand curves for a hybrid automotive system, testing twelve configurations with three different energy management strategies and four values for the degree of hybridization (DOH), the latter representing the share of the total power of the vehicle powertrain supplied by the battery. The first control logic (Battery Main—BTM) uses mainly batteries to satisfy the power demand and fuel cells as backup, while in the other two controllers, fuel cells operate continuously (Fuel Cell Main—FCM) or within a fixed range (Fuel Cell Fixed—FCF) using batteries as backup. The results are assessed in terms of H2 consumption, overall system efficiency, and fuel cell predicted lifespan. The battery is heavily stressed in the BTM and FCF logics, while the FCM logic uses the battery only occasionally to cover load peaks. This is reflected in the battery’s State of Charge (SOC), indicating different battery stress levels between the BTM and FCF modes. The FCF logic has higher stress levels due to load demand, reducing battery lifetime. In the BTM and FCM modes, the fuel cell operates with variable power, while in the FCF mode, the fuel cell operates in a range between 90 and 105% of its rated power to ensure its lifetime. In the BTM and FCM modes, hydrogen consumption decreases at almost the same rate as the DOH increases, due to a decrease in battery capacity and a smaller amount of hydrogen being used to recharge it. In contrast, the FCF control logic results in a larger fuel consumption when the DOH decreases. In terms of FC durability, the FCF control logic performs better, with a predicted lifetime ranging from 1815 h for DOH = 0.5 to 2428 h for DOH = 0.1. The FCM logic has the worst performance, with a predicted lifetime of 800 to 808 h, being almost insensitive to the DOH variation. Simulations were performed on two different driving cycles, and similar trends were observed. Simulations taking into account fuel cell (FC) performance degradation showed an increase in hydrogen consumption of approximately 38% after 12 years. Overall, this study highlights the importance of optimizing control systems to improve the performance of fuel cell hybrid vehicles, also taking into account the component of performance degradation.

Decarbonization will allow the automotive sector to achieve net-zero greenhouse gases emissions. Electric and hydrogen vehicles will contribute to that final target. Fuel Cell Hybrid Electric Vehicles FCHEVs aim at solving some of the issues of the otherwise standalone options: higher range in comparison with Battery Electric Vehicles, and allowing the fuel cell to be downsized, operated at greater efficiency, and less exposed to degradation. In this paper, a FCHEV Digital Twin DT is proposed to characterize the vehicle behavior during the WLTP driving cycle with accurate modeling of the auxiliary systems. Two control strategies, Range Extender and optimized Fuzzy logic control, are compared to show the impact on the vehicle and components performance and highlight the impact, energy-wise, of such systems in the Balance of Plant. Increased range by nearly 30 km is demonstrated while simultaneously limiting load stresses on the battery pack. • Detailed modeling of Fuel Cell Hybrid Electric Vehicle (powertrain and auxiliaries). • Vehicle auxiliaries account for almost 35–45% of the total energy consumption. • Ambient temperature strongly impacts on vehicle range (up to 13% of reduction). • HVAC is the most impacting auxiliary subsystem from energy standpoint. • Optimized fuzzy logic control increases range up to 4.5% respect to Range Extender. [ABSTRACT FROM AUTHOR]

The Intergovernmental Panel on Climate Change (IPCC) has concluded that climate change is caused by human activities. This case study presents findings on the vehicle use by the Department of Health in Ekurhuleni, Gauteng province, South Africa. The objectives of this study are to estimate the carbon dioxide equivalent emissions of government fleet vehicles and to identify mitigation measures to reduce the vehicle carbon emissions. Both the World Resource Institute Greenhouse Gas Protocol (GHGP) and the United Kingdom Department of Environmental Forestry and Rural Affairs (DEFRA) methodologies were used. The study revealed that the government fleet vehicles emitted 1362 t CO2e for a five year period (2010 − 2014), which is equivalent to $ 9 071 of the South African carbon tax. Various measures to reduce CO2e emissions were recommended, money saving from fuel and potential revenue generating opportunities were identified, including the use of hybrid vehicles. [ABSTRACT FROM AUTHOR]

The automotive sector has been experiencing a rapid development in recent times. Modern trends aim at the progress of so-called sustainable, eco-friendly vehicles, in many cases associated with advanced technologies and assistance systems. It is increasingly common to see cars with electric, hybrid, gas or hydrogen propulsion systems. Such approaches can create a transformation of manufacturing processes towards the growth of new types and fields of technologies and systems in the automotive industry. The manuscript discusses the subject of vehicles with various types of power supply, i.e., propulsion system. The investigation was executed with different respondent groups whereby the analysis was performed predominantly by using two merging criteria such as place of residence and gender of respondents. Following the research conducted, we state that given a variety of variables, the majority of the respondents are convinced that, prospectively, electric and hybrid vehicles in all probability will be the prevailing types of vehicles occurring on the roads of the Czech Republic. However, it is also important to analyze the situation of the current access to energy resources for manufacturing of both kinds of vehicles and, above all, their utilization. Thus, the preferences of drivers are key issues, but it is also necessary to take into consideration the production capacity and investment profitability regarding the purchase of vehicles with modern types of propulsion system. [ABSTRACT FROM AUTHOR]

The transportation sector has the highest energy demand worldwide and bears the primary responsibility for CO2 emissions. Electromobility has emerged as the most feasible way to alleviate this problem. However, its potential depends heavily on the development of renewable energies. Island regions raise additional barriers to electromobility due to their heavy dependence on fossil fuels. This article addresses this challenge by presenting a comprehensive well-to-wheel framework to assess the levels of efficiency and CO2 emissions of electromobility options such as battery and plug-in electric vehicles (BEVs and PHEVs). The results were compared with those for internal combustion engine vehicles (ICEVs). The framework proposed takes account of various factors including the extraction, refining, and transport of oil, different segments of land vehicles, and electricity system operations. The framework is demonstrated with a case study of the Spanish Canary archipelago. The results show that BEVs improve efficiency and CO2 emissions by around 30% compared to ICEVs on islands where the share of renewable energies is higher than 21%. In contrast, limited renewable generation may lead to BEVs polluting up to 15% more than ICEVs. PHEVs should be considered as a suitable alternative if the share of renewable generation is higher than 35%. [ABSTRACT FROM AUTHOR]

The current understanding of CO2 emission concentrations in hybrid vehicles (HVs) is limited, due to the complexity of the constant changes in their power-train sources. This study aims to address this problem by examining the accuracy, speed and size of traditional and advanced machine learning (ML) models for predicting CO2 emissions in HVs. A new long short-term memory (LSTM)-based model called UWS-LSTM has been developed to overcome the deficiencies of existing models. The dataset collected includes more than 20 parameters, and an extensive input feature optimization has been conducted to determine the most effective parameters. The results indicate that the UWS-LSTM model outperforms traditional ML and artificial neural network (ANN)-based models by achieving 97.5% accuracy. Furthermore, to demonstrate the efficiency of the proposed model, the CO2-concentration predictor has been implemented in a low-powered IoT device embedded in a commercial HV, resulting in rapid predictions with an average latency of 21.64 ms per prediction. The proposed algorithm is fast, accurate and computationally efficient, and it is anticipated that it will make a significant contribution to the field of smart vehicle applications. [ABSTRACT FROM AUTHOR]

Reduction of CO2 emissions is a prevalent subject in the transportation sector. Cylinder deactivation (CDA) provides a method to reduce CO2 emissions at part load. However, there is little consideration of how these strategies affect catalyst performance.Effects of two CDA strategies on catalyst performance were studied. The first strategy of open-loop lambda control CDA improved catalyst CO conversion to 100 % and prevented NH3 formation over the catalyst. There was a NOX penalty if the duration exceeded 5 seconds. The closed-loop CDA strategy increased catalyst temperature by 300°C for durations of 60 seconds.Open-loop CDA can prevent NH3 formation and improve CO conversion. Closed-loop CDA strategy has potential to increase catalyst temperature and be effective at reducing light-off during cold starts without additional hardware. This gives the strategy an advantage over more complex heating options. Both strategies provide opportunities to help meet current and future emission regulations.

Due to the rapid expansion of electric vehicles (EVs), they are expected to be one of the main contributors to transportation. The increasing use of fossil fuels as one of the most available energy sources has led to the emission of greenhouse gases, which will play a vital role in achieving a sustainable transportation system. Developed and developing countries have long-term plans and policies to use EVs instead of internal combustion vehicles and to use renewable energy to generate electricity, which increases the number of charging stations. Recently, to meet the charging demand for EVs, the main focus of researchers has been on smart charging solutions. In addition, maintaining power quality and peak demand for grids has become very difficult due to the widespread deployment of EVs as personal and commercial vehicles. This paper provides information on EV charging control that can be used to improve the design and implementation of charging station infrastructure. An in-depth analysis of EV types, global charging standards, and the architectures of AC-DC and DC-DC converters are covered in this review article. In addition, investigating the role of EV collectors, as well as EV penetration, in electric energy systems to facilitate the integration of electric energy systems with renewable energy sources is one of the main goals of this paper. [ABSTRACT FROM AUTHOR]

Hydrogen electric locomotives are receiving growing attention and progressing towards net zero. This letter discusses the improvement of traditional diesel-electric locomotives to use hydrogen and reduce energy demand. An internal combustion engine featuring direct injection and jet ignition of the hydrogen is proposed. The four-strokes, 12 L, V12 engine achieves peak power of 750 kW and peak efficiency above 46%. The propulsion system may be further optimized by adopting battery energy storage to buffer the operation of the engine and provide extra power when accelerating. This way, the engine may be further optimized to work over a narrower range of speeds and loads and be made smaller to provide reduced power. • Conversion of diesel locomotives to hydrogen is straightforward. • Use of a larger traction battery help with energy recovery. • It also helps using a smaller engine to work more efficiently. • Fuel cell alternative has efficiency advantage, but weight, volume, power density, and TRL disadvantages. [ABSTRACT FROM AUTHOR]

Energy management in electrified vehicles is critical and directly impacts the global operating efficiency, durability, driveability, and safety of the vehicle powertrain. Given the multitude of components of these powertrains, the complexity of the proper control is significantly higher than the conventional internal combustion engine vehicle (ICEV). Hence, several control algorithms and numerical methods have been developed and implemented in order to optimize the operation of the hybrid powertrain while complying with the required boundary conditions. In this work, a model-based method is used for predicting the impacts of a set of possible control actions, choosing the one minimizing the associated costs. In particular, the energy management technique used in the present study is the equivalent consumption minimization strategy (ECMS). The novelty of this work consists of taking into account the thermal state of the ICE for optimization. This feature was implemented by means of an extensive experimental campaign at different coolant temperatures of the ICE to calibrate the additional fuel consumption due to operating the engine outside of its optimum temperature. The results showed significant gains in both WLTC and RDE cycles. [ABSTRACT FROM AUTHOR]

Hybrid vehicles account for the largest share of new motor vehicle sales in Europe. These are vehicles that are expected to bridge the technological gap between vehicles with internal combustion engines and electric vehicles. Such a solution also makes it possible to meet the limits of motor vehicle emissions, at a time when it is particularly important to test them under actual traffic conditions. This article analyzes the impact of the length of the test routes in relation to current, but also future regulations of approval standards. Three routes of post-phase composition (urban, rural, motorway) with lengths of about 30, 16 and 8 km were selected for the study. Measurements of the main emission components were made using portable emission measurement systems (PEMS), and exhaust emissions were determined using the moving average window (MAW) method. Analysis of the obtained results led to the conclusion that the current requirements for the RDE test (in particular, the duration of the test) enforce a length of each part of 32 km. Reducing the test to 60–90 min causes the individual phases to last 16 km, and the main advantage of such a solution is the very strong influence of the cold start phase on the emission results in the urban phase. Future declarations by lawmakers to drastically reduce the length of the test phases to 8 km will force hybrid vehicles to be tested largely using the internal combustion engine. This will be the right thing to do, especially in the urban phase, as now in addition to a significant reduction in the engine warm-up phase, manufacturers will have to take into account that such an engine thermal condition can also occur in the rural phase. [ABSTRACT FROM AUTHOR]

Hybrid electric vehicles are promising solutions to the need for cleaner transport. Their ability to drive fully electric also opens the possibility of zero local emission operation by turning off the internal combustion engine. However, prolonged periods with the engine turned off result in a cooldown of the aftertreatment system resulting in increased emissions when the engine is restarted. To remedy this problem, an emission management strategy that, based on pre-heating of the aftertreatment system, aims to reduce the impact of a prolonged engine-off event on NO x emissions is developed. The method works by locating each engine-off event and then handling each event separately using an optimization scheme that combines pre-heating and a causal heuristic emission management strategy. The individual events are linked using an equivalence factor that describes the decided trade-off between fuel and NO x . The equivalence factor can be chosen heuristically or iteratively to give the desired result in terms of NO x reduction and fuel consumption. The strategy is evaluated using simulations of a drayage drive cycle with multiple engine-off events. The results from the simulations show that for engine-off times below 0.5 h the strategy can reduce NO x compared to the baseline strategy while using the same amount of fuel. If the strategy is allowed more fuel, significant reductions in NO x can be seen for engine-off times up to 1.5 h, after which an exponential decay in the effectivity of the strategy is observed. It is also shown that the reduction in NO x is fairly linear in the equivalence factor, which gives the procedure of choosing it a predictable behavior. [ABSTRACT FROM AUTHOR]

The authors compare the energy consumption and CO2 emissions from vehicles using internal combustion engines (ICE), battery electric vehicles (BEV), fuel cell electric vehicles (FCEV), and two types of hybrid vehicles, BEV-ICE hybrid and BEV-FCEV hybrid. This paper considers several scenarios for four countries' electricity production from primary energy sources to estimate total CO2 release. Energy consumption of the vehicle per 100 km, emissions during manufacturing, battery production, and lifecycle of the vehicle are considered in the total amount evaluation of CO2 released. The results show that with current technologies for battery manufacturing, and a significant proportion of national grid electricity delivered by fossil fuels, BEV is the best choice to reduce carbon emissions for shorter driving ranges. In the case of electricity generation mainly by low-carbon sources, FCEV and BEV-FCEV hybrid vehicles end up with lower carbon dioxide emissions. In contrast, with electricity mainly generated from fossil fuels, electric vehicles do not reduce CO2 emissions compared to combustion cars. [ABSTRACT FROM AUTHOR]

[Display omitted] As the ownership of hybrid vehicles soars, accurately predicting and assessing CO 2 emissions become crucial. This study utilized the AVL portable emission measurement system (PEMS) to reveal the actual CO 2 emission of three types of hybrid vehicles. Firstly, engine speed is a key factor influencing CO 2 emissions of range-extended electric vehicle (REEV) and plug-in hybrid electric vehicle (PHEV), while vehicle specific power (VSP) affects HEV. Secondly, in terms of fuel consumption, when the battery levels of REEV and PHEV are low, their fuel consumption tends to be higher than that of HEV. Specifically, the CO₂ emission factor (the amount of CO 2 emitted by a vehicle per unit distance during operation) ratios of REEV to PHEV range from 1.19 to 1.89, while the ratios of REEV to HEV are between 1.41 and 2.57. Thirdly, in terms of NO X control, HEV performed significantly worse. [ABSTRACT FROM AUTHOR]

In the past few years, it can be seen that the automotive market has been developing quite rapidly, especially when it comes to electric cars. This is because the development of sustainable cars seems to be an extremely important issue at the moment. Nowadays, cars with different propulsion systems (among others electric, hybrid, gas, or hydrogen) can be met on the roads. But, political action is mainly aimed at electric cars. Such an approach will certainly lead to fundamental changes in production processes in the near future via the emergence and development of new technologies in the field of electric passenger cars. Therefore, the manuscript discusses the concept of vehicles with different types of power supply, with the main emphasis on electric vehicles. The essence of electric vehicles, their genesis, rationale for development, and growth are indicated. The different markets around the world, through the prism of, on the one hand, programs supporting the purchase and use of this type of vehicle and, on the other hand, factors limiting and inhibiting their uptake, are also discussed. The research was conducted in a group of both current and potential drivers from Eastern Poland, with different categories of grouping variables used in the analyses. On the basis of the research carried out and the results obtained, it can be argued that due to various factors, the respondents’ opinions are varied, and there are no unambiguous conclusions stating that such solutions will soon be available. Indeed, a number of doubts and barriers were noted among respondents. Driver preferences are therefore a key issue, but production capacity and the profitability of investments in the purchase of vehicles with an electric power supply should also be taken into account.

Exploiting the full potential of hybrid electric vehicles (HEVs) requires suitable (i) route selection and (ii) power management. Due to coupling of the two subproblems, an integrated optimization problem is desired, i.e., optimizing simultaneously the route selection and the split between combustion engine and electric motor over the entire route selection. The resulting optimal route and vehicle operation can be used as a basis for a subordinate vehicle controller. We present an eco-routing approach that embeds a hybrid (mechanistic/data-driven) model of the HEV powertrain in an integrated routing and power management optimization problem. Formulating the integrated routing problem with the hybrid model yields a mixed-integer bilinear program which we reformulate and solve a mixed-integer linear program using a state-of-the-art solver. The results show the validity of the developed hybrid powertrain model and demonstrate that the eco routing approach with the powertrain model embedded can be applied to large-scale problems. We consider optimization for minimal travel time and minimum fuel consumption. The latter results in fuel demand reductions up to 70 %. Alternatively, we minimize the fuel consumption while constraining the travel time to a maximum value resulting in up to 50 % fuel demand reductions. The highest fuel demand reductions are achieved in urban environments. The entire framework is written in python and provided as an open-source version (MIT License) under https://git.rwth-aachen.de/avt-svt/public/optimal-routing that can readily be applied. [ABSTRACT FROM AUTHOR]

Battery is essential parts of an electric and hybrid electric vehicle. Good amount of heat is generated by charging and discharging actions. For maximum efficiency, reliability of utmost necessary to conserve the optimum temperature by employing a proper battery thermal management system. Uses of Phase Change Materials for thermal management have attracted attention in recent years due to its lightweight, improved energy efficiency, less intricacy and better thermal homogeneity. These materials are a potential substitute for economical, and simple operation. Phase Change Materials could be utilized as active or passive systems, empowering the universal system to nurture near-autonomous performances. This work consists of the discussions on battery thermal management systems using phase change materials, enhancement of Phase Change Materials’ thermal conductivity, thermal management schemes and finally concluding with the application sections. Heat transfer can be augmented by application of Phase Change Materials through thermally conductive particles, metal fin, metal foam and expanded graphite matrix. Newly developed thermal management configurations like multi-layer Phase Change Materials and sandwiches are also outlined. Additionally, a thermal management system merging Phase Change Material cooling via air or liquid is also presented.

Plug-in hybrid electric vehicles (PHEVs) are a promising technology for reducing the tailpipe emissions of CO2 as well as air pollutants, especially in urban environments. However, several studies raise questions over their after-treatment exhaust efficiency when their internal combustion engine (ICE) ignites. The rationale is the high ICE load during the cold start in combination with the cold conditions of the after-treatment devices. In this study, we measured the solid particle number (SPN) emissions of two Euro 6d and one Euro 6d-TEMP gasoline direct injection (GDI) PHEVs (electric range 52–61 km) all equipped with a gasoline particulate filter, in the laboratory and on-road with different states of charge of the rechargeable electric energy storage system (REESS) and ambient temperatures. All vehicles met the regulation limits but it was observed that, even for fully charged REESS, when the ICE ignited SPN emissions were similar or even higher in some cases compared to the operation of these vehicles solely with their ICE (discharged REESS) and also when compared to conventional GDI vehicles. On-road SPN emission rate spikes during the first 30 s after a cold start were, on average, 2 to 15 times higher with charged compared to discharged REESS due to higher SPN concentrations and exhaust flow rates. For one vehicle in the laboratory under identical driving conditions, the ICE ignition at high load resulted in 10-times-higher SPN emission rate spikes at cold-start compared to hot-start. At −10 °C, for all tested vehicles, the ICE ignited at the beginning of the cycle even when the REESS was fully charged, and SPN emissions increased from 30% to 80% compared to the cycle at 23 °C in which the ICE ignited. The concentration of particles below 23 nm, which is the currently regulated lower particle size, was low (≤18%), showing that particles larger than 23 nm were mainly emitted irrespective of cold or hot engine operation and ambient temperature. [ABSTRACT FROM AUTHOR]

The automotive sector has been experiencing a rapid development in recent times. Modern trends aim at the progress of so-called sustainable, eco-friendly vehicles, in many cases associated with advanced technologies and assistance systems. It is increasingly common to see cars with electric, hybrid, gas or hydrogen propulsion systems. Such approaches can create a transformation of manufacturing processes towards the growth of new types and fields of technologies and systems in the automotive industry. The manuscript discusses the subject of vehicles with various types of power supply, i.e., propulsion system. The investigation was executed with different respondent groups whereby the analysis was performed predominantly by using two merging criteria such as place of residence and gender of respondents. Following the research conducted, we state that given a variety of variables, the majority of the respondents are convinced that, prospectively, electric and hybrid vehicles in all probability will be the prevailing types of vehicles occurring on the roads of the Czech Republic. However, it is also important to analyze the situation of the current access to energy resources for manufacturing of both kinds of vehicles and, above all, their utilization. Thus, the preferences of drivers are key issues, but it is also necessary to take into consideration the production capacity and investment profitability regarding the purchase of vehicles with modern types of propulsion system.

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Extensive environmental protection activities include the promotion of alternative drive systems for motor vehicles. An important role in this field is played by hybrid vehicles, with their low operation costs being a strong marketing argument. Can such economies be conducive to the intensity of use of hybrid vehicles compared with vehicles with conventional drive systems? To answer this question, the intensity of use of hybrid vehicles was observed in a few different countries. The attention was focused on the occurrence of extreme (very low and very high) mileage values within comparable vehicle groups. The survey carried out has revealed distinct differences in the intensity of use of hybrid vehicles compared with motor vehicles with conventional drive systems (IC). The average mileage values for hybrid vehicles are higher than those recorded for conventional ones during the same period, but this difference can only be seen in the initial period of vehicle use, rapidly decreasing with vehicle operation years. The share of vehicles with extreme mileage values recorded during the period under observation, presented in the paper in several ways, declines with the years of vehicle use. In spite of that, however, the percentage of vehicles with extreme mileage values is high in HVs group against IC. [ABSTRACT FROM AUTHOR]

In the last decade, a great effort has been employed in the study of Hybrid Unmanned Aerial Underwater Vehicles, robots that can easily fly and dive into the water with different levels of mechanical adaptation. However, most of this literature is concentrated on physical design, practical issues of construction, and, more recently, low-level control strategies. Little has been done in the context of high-level intelligence, such as motion planning and interactions with the real world. Therefore, we proposed in this paper a trajectory planning approach that allows collision avoidance against unknown obstacles and smooth transitions between aerial and aquatic media. Our method is based on a variant of the classic Rapidly-exploring Random Tree, whose main advantages are the capability to deal with obstacles, complex nonlinear dynamics, model uncertainties, and external disturbances. The approach uses the dynamic model of the HyDrone, a hybrid vehicle proposed with high underwater performance, but we believe it can be easily generalized to other types of aerial/aquatic platforms. In the experimental section, we present simulated results in environments filled with obstacles, where the robot is commanded to perform different media movements, demonstrating the applicability of our strategy. [ABSTRACT FROM AUTHOR]

KAITLYN TRADD Mechanical Engineer, Applied Ocean Physics and Engineering SINCE I CAME TO WHOI TWELVE YEARS AGO, I'VE RUN THE GAMUT OF ROBOTICS PROJECTS. I sailed with ROVs Jason and [...]

Recovering solar energy during parking phases can significantly improve light-duty vehicles' fuel economy (FE) and help in reducing greenhouse gas impact and harmful tailpipe emissions. Nevertheless, the contribution due to off-driving photovoltaic (PV) recharging shall be adequately accounted for when approaching the development and testing of energy-efficient and environmentfriendly powertrain energy management. The aim of this work was thus to enhance the existing highly charge-depleting (HCD) control strategy of a 48V mild-hybrid electric vehicle (MHEV), implementing a state-of-charge-dependent soft charge-depleting (SCD) one. The performance of the implemented control strategy was analyzed on two different vehicle configurations, obtained by integrating a solar kit with the aforementioned mild-hybrid powertrain. The modelling framework used to perform simulation-based analysis was suitably updated in such a way as to test both charge-depleting and quasi-charge-sustaining strategies. A scenario analysis was thus enabled, whose objective was to assess the FE and carbon dioxide (CO2) reduction potential associated with the joint effect of solar hybridization and the proposed battery state-of-chargedriven control rules. The Federal Urban Driving Schedule (FUDS) was simulated for the four vehicle scenarios available (conventional, MHEV-HCD, MHEV-SCD, and solar mild hybrid). The results confirmed the high potential of solar-assisted mild-hybridization of original conventional vehicles, with significant benefits (i.e., about 30% improvement) achieved both in terms of FE and CO2 emissions. [ABSTRACT FROM AUTHOR]

Multimode hybrid powertrains have captured the attention of automotive OEMs for their flexible nature and ability to provide better and optimized efficiency levels. However, the presence of multiple actuators, with different efficiency and dynamic characteristics, increases the problem complexity for minimizing the overall power losses in each powertrain operating condition. The paper aims at providing a methodology to select the powertrain mode and set the reference torques and angular speeds for each actuator, based on the power-weighted efficiency concept. The power-weighted efficiency is formulated to normalize the efficiency contribution from each power source and to include the inertial properties of the powertrain components as well as the vehicle motion resistance forces. The approach, valid for a wide category of multimode powertrain architectures, is then applied to the specific case of a two-mode hybrid system where the engagement of one of the two clutches enables an Input Split or Compound Split operative mode. The simulation results obtained with the procedure prove to be promising in avoiding excessive accelerations, drift of powertrain components, and in managing the power flow for uphill and downhill vehicle conditions. [ABSTRACT FROM AUTHOR]

Battery Electric Vehicles (BEVs) have been in the market for over 10 years; however, their market diffusion has been slow despite their environmental and social advantages. Their high purchase cost is one of the most significant barriers towards their wider adoption. Policy makers have used the Total Cost of Ownership (TCO) estimate to expose the lower fuel and maintenance cost of BEVs relative to gasoline-based vehicles. In this paper, a model is developed for private consumers on the principles of the TCO that assesses different vehicle technologies and incorporates the consumers' preferences when purchasing a new vehicle. The TCO model is applied on three representative vehicle technologies, including an Internal Combustion Engine Vehicle (ICEV), a Hybrid Electric Vehicle (HEV) and a BEV; for three vehicle classes (i.e., small, medium and SUV), resulting in the assessment of nine vehicle models. The TCO is quantified by using data for France. A weighted TCO per vehicle is also estimated by using the Analytic Hierarchy Process (AHP) to incorporate the consumers' preference on TCO parameters. The TCO and the Weighted Average Cost (WAC) estimates for each vehicle are used to assess the nine vehicle models and compare results. The ICEV has the lowest TCO for the small and medium classes, while the BEV is ranked as the most economic vehicle for the SUV class. As the WAC is greatly influenced by the purchase cost, vehicle rankings change for only one class. Our method suggests that a dynamic TCO should capture consumers' preferences and support policy makers to adjust incentives at local level. [ABSTRACT FROM AUTHOR]

The transportation sector has the highest energy demand worldwide and bears the primary responsibility for CO2 emissions. Electromobility has emerged as the most feasible way to alleviate this problem. However, its potential depends heavily on the development of renewable energies. Island regions raise additional barriers to electromobility due to their heavy dependence on fossil fuels. This article addresses this challenge by presenting a comprehensive well-to-wheel framework to assess the levels of efficiency and CO2 emissions of electromobility options such as battery and plug-in electric vehicles (BEVs and PHEVs). The results were compared with those for internal combustion engine vehicles (ICEVs). The framework proposed takes account of various factors including the extraction, refining, and transport of oil, different segments of land vehicles, and electricity system operations. The framework is demonstrated with a case study of the Spanish Canary archipelago. The results show that BEVs improve efficiency and CO2 emissions by around 30% compared to ICEVs on islands where the share of renewable energies is higher than 21%. In contrast, limited renewable generation may lead to BEVs polluting up to 15% more than ICEVs. PHEVs should be considered as a suitable alternative if the share of renewable generation is higher than 35%.

The current understanding of CO2 emission concentrations in hybrid vehicles (HVs) is limited, due to the complexity of the constant changes in their power-train sources. This study aims to address this problem by examining the accuracy, speed and size of traditional and advanced machine learning (ML) models for predicting CO2 emissions in HVs. A new long short-term memory (LSTM)-based model called UWS-LSTM has been developed to overcome the deficiencies of existing models. The dataset collected includes more than 20 parameters, and an extensive input feature optimization has been conducted to determine the most effective parameters. The results indicate that the UWS-LSTM model outperforms traditional ML and artificial neural network (ANN)-based models by achieving 97.5% accuracy. Furthermore, to demonstrate the efficiency of the proposed model, the CO2-concentration predictor has been implemented in a low-powered IoT device embedded in a commercial HV, resulting in rapid predictions with an average latency of 21.64 ms per prediction. The proposed algorithm is fast, accurate and computationally efficient, and it is anticipated that it will make a significant contribution to the field of smart vehicle applications.