To improve braking performance and regenerative energy of front drive electric vehicles (EVs) driven by switched reluctance motor (SRM), a regenerative braking control strategy based on multi-objective optimization of switched reluctance generator (SRG) drive system is proposed in this paper. Firstly, a partition braking force distribution strategy is developed by jointly considering braking energy and safety, and SRG drive system model is established based on low and high-speed condition. The vehicle braking system model including mechanic and regenerative braking system is built. Then, a multi-objective optimization function with three weight factors is defined, where output generated power, torque smoothness, and current smoothness are selected as optimization objectives to improve the driving range, braking comfort, and battery lifetime, respectively. Furthermore, a multi-objective optimization controller with variable switch angles is designed and combined with vehicle braking system. Finally, braking energy recovery efficiency, braking smoothness, and charging current smoothness under the multi-objective optimization controller for SRG are analyzed and compared with those under output power optimization controller. The comparison results show that the regenerative braking control strategy based on multi-objective optimization of SRG can effectively increase the vehicle braking comfort and improve battery lifetime without decreasing recovery energy.

To improve the mechanical performance of the In‐wheel switched reluctance motor (SRM) used in electric vehicles (EVs), structure design and geometrical multi‐objective optimisation strategy for the In‐wheel SRM were developed in this study. The design method for major parameters of the In‐wheel SRM was presented by means of design specifications of the EVs. According to requirements of the EVs, four indicators of the SRM were defined to evaluate the development of the SRM and perform the optimisation. To simultaneously improve the static performance of the SRM, a novel multi‐objective simultaneous optimisation function was proposed by using four weighted factors and considering sensitivity analysis of the design variables on indicators. A four‐phase 16/20 In‐wheel SRM with an outer rotor was designed and optimised based on the proposed multi‐objective optimisation method. The influence of design variables on average torque, torque ripple, efficiency, and torque density was analysed based on a combination of finite element analysis and orthogonal experiment design method. The static and dynamic torque performances of the optimised SRM were evaluated and compared with those of the initial motor. The comparison results showed that the proposed multi‐objective simultaneous optimisation strategy can greatly improve the static and dynamic torque performances of the SRM.

The in-wheel switched reluctance motor (IWSRM) has significant potential for utilization in electric vehicle (EV) because of its inherent advantages such as low cost, robustness, wide speed range, and direct drive mode. However, the unbalanced radial force caused by eccentricity of IWSRM results in increasing vehicle vibration and decreasing riding comfort. In this paper, various vertical vibration control strategies for IWSRM are proposed and compared to improve the vibratory behavior of vehicle. First, effects of eccentricity ratio and eccentric angle on radial force, torque, and inductance are investigated by numerical analysis method for IWSRM. Then, IWSRM model, vehicle model, and suspension model are developed, based on which two common control algorithms (i.e. CCC and PWM) are provided and used as benchmarks to compare with the newly proposed two (i.e. CCC-F and PWM-F). They are designed by introducing the vehicle vertical acceleration as an extra control objective. Finally, the dynamic response of four control strategies are analyzed and the comparison results show that each of them performs differently under different driving conditions. As a result, a switchable controller based on the proposed control algorithms is presented to improve the overall performance of the IWSRM for EVs under various driving modes.

To improve the comprehensive performance of the electromechanical coupling braking system (CBS) and suppress vertical vibration caused by the unbalanced radial forces of in-wheel motors, a CBS control strategy based on multiobjective optimization on the control parameters of switched reluctance motor (SRM) drive system is proposed in this article. First, the electromagnetic coupling and eccentricity characteristics of SRM are analyzed, and a multiobjective optimization strategy (MOOS) for the SRM-drive system is proposed to comprehensively improve the endurance mileage, battery life, and braking comfort. Then, switch angles and required regenerative braking force are optimized by the combination of MOOS and genetic algorithm, and the corresponding optimized controllers are established. Furthermore, the braking performance of optimized CBS is analyzed and compared to the other three single-objective optimization strategies (SOOSs), and the results indicate that the control strategy with MOOS can improve vehicle comprehensive performance, although the strategies with SOOSs have a great improvement for corresponding objectives. Meanwhile, based on the strategies, comprehensive switchable control logic is proposed to improve the overall performance of vehicles under different braking modes. Finally, the results from the simulation and processor in loop test are analyzed and compared, which validates the real-time performance and effectiveness of the control strategy.

Compared with the single‐phase excitation mode of the switched reluctance motor (SRM), the statictorque curves of the SRM with two‐phase excitation mode are more flexuous andwide flat regions are absent from the curves. To improve the static torqueperformance of the SRM with two‐phase mode, geometrical multi‐objectiveoptimisation strategy is developed in this paper. Considering the requirementsof the electric vehicles, four indicators are presented and defined to evaluatethe development of the SRM. Six main independent variables are determined and anovel multi‐objective optimisation function was proposed to simultaneouslyimprove static performance of the SRM. Furthermore, to simplify theoptimisation, a sensitivity index that reflects the relative importance of eachvariable is developed to eliminate insignificant variables. The four‐phase 8/6SRM with two‐phase mode is optimised by means of the proposed multi‐objectiveoptimisation method based on effects and sensitivity analysis of the designvariables on indicators. The static and dynamic torque performance of theoptimised SRM is evaluated and compared with those of the initial motor. Thecomparison results show that the multi‐objective simultaneous optimisationstrategy can improve the static average torque, static average torque per mass,and global index by 18.09, 12.08, and 6.57%,respectively.