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Copyright of Journal of South China University of Technology (Natural Science Edition) is the property of South China University of Technology 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.)

Copyright of Automobile Technology is the property of Automobile Technology Editorial Office 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 order to solve the problem of insufficient range caused by the excessive weight of the pure electric bus, a multi-objective genetic algorithm (GA) and radial basis function (RBF) model are combined in this paper to realize the lightweighting of steel and aluminum hybrid body of the pure electric bus. First, the upper and lower frames of the pure electric bus body are initially designed with aluminum alloy and steel materials respectively to meet the lightweight requirements. Second, a finite element (FE) model of the bus body is established, and the validity of the model is validated through physical tests. Then, the sensitivity analysis is performed to identify the relative importance of individual design parameters over the entire domain. The Hamosilei sampling method is selected for the design of the experiment (DOE) because users can specify the number of experiments and ensure that the set of random numbers is a good representative of real variability, and the RBF model is adopted to approximate the responses of objectives and constraints. Finally, the multi-objective optimization (MOO) method based on GA with RBF model is used to solve the optimization problem of the lightweight steel-aluminum hybrid bus body. The results show that compared with the traditional fully steel body, the use of the aluminum alloy lower-frame structure can reduce body mass by 38.4%, and the proposed optimization method can further reduce the mass of the steel-aluminum body to 4.28% without affecting the structural stiffness and strength performance of the body.

In order to solve the problem of insufficient range caused by the excessive weight of the pure electric bus, a multi-objective genetic algorithm (GA) and radial basis function (RBF) model are combined in this paper to realize the lightweighting of steel and aluminum hybrid body of the pure electric bus. First, the upper and lower frames of the pure electric bus body are initially designed with aluminum alloy and steel materials respectively to meet the lightweight requirements. Second, a finite element (FE) model of the bus body is established, and the validity of the model is validated through physical tests. Then, the sensitivity analysis is performed to identify the relative importance of individual design parameters over the entire domain. The Hamosilei sampling method is selected for the design of the experiment (DOE) because users can specify the number of experiments and ensure that the set of random numbers is a good representative of real variability, and the RBF model is adopted to approximate the responses of objectives and constraints. Finally, the multi-objective optimization (MOO) method based on GA with RBF model is used to solve the optimization problem of the lightweight steel-aluminum hybrid bus body. The results show that compared with the traditional fully steel body, the use of the aluminum alloy lower-frame structure can reduce body mass by 38.4%, and the proposed optimization method can further reduce the mass of the steel-aluminum body to 4.28% without affecting the structural stiffness and strength performance of the body. [ABSTRACT FROM AUTHOR]

Accurate and reasonable matching design is a current and difficult point in electric vehicle research. This paper presents a parameter optimization method for the power system of a medium-sized bus based on the combination of the orthogonal test and the secondary development of ADVISOR software. According to vehicle theoretical knowledge and the requirements of the vehicle power performance index, the parameters of the vehicle power system were matched and designed. With the help of the secondary development of MATLAB/Simulink and ADVISOR software, the modeling of the key parts of the vehicle was carried out. Considering the influence of the number of battery packs, motor power model, wheel rolling resistance coefficient, and wind resistance coefficient on the design of the power system, an L9 (34)-type orthogonal table was selected to design the orthogonal test. The dynamic performance and driving range of the whole vehicle were simulated using different design schemes, and the accuracy of the simulation results was verified by comparing and analyzing the simulation images. The results demonstrated that in the environment where the wind resistance coefficient was 0.6 and the wheel rolling resistance coefficient was 0.009, with 240 sets of lithium batteries (battery energy, 264 kW h; battery capacity, 100 Ah) as the power source, the pure electric medium-sized bus equipped with the PM165 permanent magnet motor (rated power, 60 kW; rated torque, 825 N m) could obtain the best power performance and economic performance. The research content of this paper provides a certain reference for the design of shuttle buses for Nantong's bus system, effectively reduces the testing costs of the vehicle development process, and provides a new idea for the power system design of pure electric buses. [ABSTRACT FROM AUTHOR]

In order to meet the safety requirements of automobile braking, to improve the braking energy recovery rate of pure electric buses and increase their driving range, the maximum regenerative braking force that the motor can provide is used to determine the front and rear wheel friction braking force distribution curve. A parallel regenerative braking control strategy, A, is proposed to make full use of the motor performance. Aiming at the problems of low power density and short cycle life with a single power battery, a composite energy system composed of power batteries and supercapacitors is designed, and an alternative energy control strategy, D, using real-time wavelet transform control is proposed. The required power is decomposed into high-frequency components and low-frequency components by using the wavelet transform control, in which the high-frequency power is borne by the supercapacitor to avoid impact on the power battery. The simulation model was created using MATLAB/Simulink software, and the simulation was carried out under combined cycle conditions to verify the effectiveness of the control strategy. The simulation results showed that compared with the original vehicle control strategy, adopting the A regenerative braking control strategy can reduce the battery SOC drop by 5.15%, increase the relative increase by 47.9%, and improve the braking energy recovery rate. Compared with the traditional logic threshold regenerative braking control strategy, AC, the AD control strategy can effectively reduce the impact of the peak current and high-frequency demands of the power battery on the battery. The maximum output current of the battery was reduced by 39.5%. The decrease in battery SOC decreased by 0.69%, and the relative increase increased by 12.43%. The driving range and braking performance of the vehicle have thus been effectively improved. [ABSTRACT FROM AUTHOR]

The pure electric bus with multi gear transmission can effectively improve the acceleration ability and driving range. However， the design of shift schedule is faced with the problems of heavy workload， high cost and over dependence on the experience of calibration engineers. Therefore， a model-based shift schedule design method， which can effectively shorten the development cycle of shift schedule is proposed. Firstly， dynamic programming is used to optimize the shift sequence of vehicles under standard cycle conditions. Then， the shift points obtained are taken as data samples， and the shift schedule that can be directly used in vehicle controller is extracted by cluster analysis method. Finally， the effectiveness of the extracted shift schedule is verified by simulation. The simulation results show that the vehicle using the shift schedule designed in this paper can give consideration to both dynamic and economy. Compared with the original shift schedule， the cycle power consumption can be reduced by 5.51%.

Adaptive cruise control (ACC), as a driver assistant system for vehicles, not only relieves the burden of drivers, but also improves driving safety. This paper takes the intelligent pure electric city bus as the research platform, presenting a novel ACC control strategy that could comprehensively address issues of tracking capability, driving safety, energy saving, and driving comfort during vehicle following. A hierarchical control architecture is utilized in this paper. The lower controller is based on the nonlinear vehicle dynamics model and adjusts vehicle acceleration with consideration to the changes of bus mass and road slope by extended Kalman filter (EKF). The upper controller adapts Model Predictive Control (MPC) theory to solve the multi-objective optimal problem in ACC process. Cost functions are developed to balance the tracking distance, driving safety, energy consumption, and driving comfort. The simulations and Hardware-in-the-Loop (HIL) test are implemented; results show that the proposed control strategy ensured the driving safety and tracking ability of the bus, and reduced the vehicle's maximum impact to 5 m/s3 and the State of Charge (SoC) consumption by 10%. Vehicle comfort and energy economy are improved obviously. [ABSTRACT FROM AUTHOR]

To solve the coordination problem between the driving anti-skid strategy and the optimal torque distribution strategy, based on the real-time particle swarm optimization algorithm, a comprehensive torque distribution strategy with the consideration of stability and economy of vehicles was proposed. The driving anti-skid strategy with slip rate as control target could output the front and rear axle torque constraints. By the particle swarm optimization with real-time optimization as optimization method and with front and rear axle torque constraints as dynamic constraint condition, the optimal torque distribution strategy could run normally when the anti-skid strategy took effect. Based on AVL-Cruise and Simulink platform, a joint simulation model of vehicle economy was established to analyze the optimization effect. The results show that under the three selected cycle conditions, the power consumption per hundred kilometers is averagely decreased by 4. 79%, and the driving mileage is averagely increased by 5. 49%. The comprehensive torque distribution strategy can improve the fuel economy on the premise of ensuring the longitudinal stability of bus. [ABSTRACT FROM AUTHOR]

To solve the problem that the correlation characteristics between the pure electric bus failure and the main faults of motor, battery and electric control systems could not be accurately elucidated by traditional failure investigation method, a new method based on signal processing was proposed, Based on the main failure types of pure electric bus and the main faults of motor, battery and electric control systems, the causal relationship between failure types and main faults of motor, battery and electric control systems was initially established, To further clarify the system failure point, the model of the pure electric bus including motor, battery and electric control systems was established, The artificial failures of pure electric bus were modeled by setting the main faults of motor, battery and electric control systems, The signals measured easily by system were analyzed, and the typical signal characteristics of different system faults were revealed, The correlation characteristics between the pure electric bus failure and the main faults of motor, battery and electric control systems were determined, and a new failure investigation method of pure electric bus was formatted. The results show that the proposed method can effectively reveal the relationship between the pure electric bus failure types of power loss, fire and out of control and the main faults of motor, battery and electric control systems. [ABSTRACT FROM AUTHOR]

A volumetric Kalman filter estimation algorithm with good real-time accuracy and stability is used to identify the quality of electric bus and road gradient in complex environment. A dynamics model of 4-gear automated mechanical transmission is established, and an economical shift strategy is proposed which is based on the fusion of four parameters: vehicle speed, throttle opening, vehicle quality and road gradient. The simulation results show the identification algorithm proposed can identify vehicle quality and road gradient accurately without adding any sensors. The multi-parameter fusion shifting strategy developed can achieve economical shifting under the condition of guaranteeing vehicle dynamic performance, which can avoid frequent shift, reduce component wear and improve ride comfort to a great extent.

Accurate and reasonable matching design is a current and difficult point in electric vehicle research. This paper presents a parameter optimization method for the power system of a medium-sized bus based on the combination of the orthogonal test and the secondary development of ADVISOR software. According to vehicle theoretical knowledge and the requirements of the vehicle power performance index, the parameters of the vehicle power system were matched and designed. With the help of the secondary development of MATLAB/Simulink and ADVISOR software, the modeling of the key parts of the vehicle was carried out. Considering the influence of the number of battery packs, motor power model, wheel rolling resistance coefficient, and wind resistance coefficient on the design of the power system, an L9 (34)-type orthogonal table was selected to design the orthogonal test. The dynamic performance and driving range of the whole vehicle were simulated using different design schemes, and the accuracy of the simulation results was verified by comparing and analyzing the simulation images. The results demonstrated that in the environment where the wind resistance coefficient was 0.6 and the wheel rolling resistance coefficient was 0.009, with 240 sets of lithium batteries (battery energy, 264 kW h; battery capacity, 100 Ah) as the power source, the pure electric medium-sized bus equipped with the PM165 permanent magnet motor (rated power, 60 kW; rated torque, 825 N m) could obtain the best power performance and economic performance. The research content of this paper provides a certain reference for the design of shuttle buses for Nantong’s bus system, effectively reduces the testing costs of the vehicle development process, and provides a new idea for the power system design of pure electric buses.

In order to meet the safety requirements of automobile braking, to improve the braking energy recovery rate of pure electric buses and increase their driving range, the maximum regenerative braking force that the motor can provide is used to determine the front and rear wheel friction braking force distribution curve. A parallel regenerative braking control strategy, A, is proposed to make full use of the motor performance. Aiming at the problems of low power density and short cycle life with a single power battery, a composite energy system composed of power batteries and supercapacitors is designed, and an alternative energy control strategy, D, using real-time wavelet transform control is proposed. The required power is decomposed into high-frequency components and low-frequency components by using the wavelet transform control, in which the high-frequency power is borne by the supercapacitor to avoid impact on the power battery. The simulation model was created using MATLAB/Simulink software, and the simulation was carried out under combined cycle conditions to verify the effectiveness of the control strategy. The simulation results showed that compared with the original vehicle control strategy, adopting the A regenerative braking control strategy can reduce the battery SOC drop by 5.15%, increase the relative increase by 47.9%, and improve the braking energy recovery rate. Compared with the traditional logic threshold regenerative braking control strategy, AC, the AD control strategy can effectively reduce the impact of the peak current and high-frequency demands of the power battery on the battery. The maximum output current of the battery was reduced by 39.5%. The decrease in battery SOC decreased by 0.69%, and the relative increase increased by 12.43%. The driving range and braking performance of the vehicle have thus been effectively improved.

When the exhaust temperature of heat pump air conditioning system of pure electric bus is too high, the performance of the system is attenuated. In order to solve the problem, an alternative system with low pressure air supply is developed. The experimental platform is set up to reveal the main factors affecting the refrigeration and heating performance of the system. The results show that the low pressure air-supply technology can significantly reduce the exhaust temperature of the compressor [ABSTRACT FROM AUTHOR]

In order to solve the problem of serious attenuation of the performance of heat pump air conditioning system for pure electric bus at high temperature in summer and at low temperature in winter, a heat pump air conditioning system for medium-pressure air-supply pure electric bus with economizer is developed. The performance of the system working at from +50 °C to -20 °C ambient temperature and at different compressor speed is studied. The results show that the exhaust temperature of the compressor can be reduced greatly. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Harbin University of Science & Technology is the property of Journal of Harbin University of Science & Technology 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 order to solve the problem that the working state of the pure electric bus power battery is susceptible to many factors, the fuzzy logic algorithm is UBed to evaluate the working status of the pure electric bus power battery. According to the diversity and ambiguity of the working state changing of the power battery, the total voltage, temperature and the insulation resistance of power battery are selected as the evaluation parameters, the corresponding membership function and fuzzy evaluation matrix are established, and the fuzzy mathematics evaluation model is established. The working state of the power battery obtained by the evaluation model is compared with the actual working state of the research object, and the results show that the obtained results are consistent with the actual situation. It can be seen that the constructed evaluation model can realize the fault prediction of the pure electric bus battery, thereby improving the safety of the pure electric bus operation and ensuring the normal operation of the bus operation system. [ABSTRACT FROM AUTHOR]

Adaptive cruise control (ACC), as a driver assistant system for vehicles, not only relieves the burden of drivers, but also improves driving safety. This paper takes the intelligent pure electric city bus as the research platform, presenting a novel ACC control strategy that could comprehensively address issues of tracking capability, driving safety, energy saving, and driving comfort during vehicle following. A hierarchical control architecture is utilized in this paper. The lower controller is based on the nonlinear vehicle dynamics model and adjusts vehicle acceleration with consideration to the changes of bus mass and road slope by extended Kalman filter (EKF). The upper controller adapts Model Predictive Control (MPC) theory to solve the multi-objective optimal problem in ACC process. Cost functions are developed to balance the tracking distance, driving safety, energy consumption, and driving comfort. The simulations and Hardware-in-the-Loop (HIL) test are implemented; results show that the proposed control strategy ensured the driving safety and tracking ability of the bus, and reduced the vehicle’s maximum impact to 5 m/s3 and the State of Charge (SoC) consumption by 10%. Vehicle comfort and energy economy are improved obviously.

The relationship between the energy consumption of buses and traffic conditions has gradually garnered research attention with the expansion of the green transportation concept and the promotion of new energy buses. In line with these developments, this study develops a spatial–temporal estimation model of residual energy for pure electric buses with fuzzy clustering and time-series algorithms. These algorithms are based on the traffic performance index of the road sections between the nearest bus stops. Furthermore, they are established according to the positions of floating vehicles and the bus routes in combination with the energy consumption data derived from the battery management system of pure electric buses. Test results show that these estimation algorithms can accurately describe the spatial–temporal relationship between traffic performance index and the residual energy in pure electric buses. Thus, they can be applied as significant references in the analysis of traffic conditions, energy conservation, and emission reduction for buses.

In order to study the energy conservation mechanism of the EHPS (Electric Hydraulic Power Steering), this paper builds an EHPS system experimental platform, including the master control platform, the test system module, the steering resistance hydraulic loading module and the EHPS system energy consumption. Based on the test of the energy consumption of the above major components, key factors influencing the energy consumption of the EHPS system is studied. Test results suggest that the non-steering and low-steering demands of the EPHS system have a huge influence on the overall energy consumption of the EHPS system. These research findings are of guiding significance to the development of new-type energy-saving EHPS system. [ABSTRACT FROM AUTHOR]

In order to realize a quick, smooth, precise shifting process of AMT used on a pure electric bus, the pure electric bus driven by AC motor is taken as the research platform. On the base of analysis of control method for shifting process of AMT without clutch and research of shifting control method of AMT actuators driven by motors, the AMT without clutch was developed for pure electric bus. With the result of conducting field test and on road test, it is obvious that the shifting performance of the pure electric bus is significantly improved. [ABSTRACT FROM AUTHOR]