To optimize the torque distribution of each drive wheel of a distributed In-wheel motor car, this paper proposes an in-wheel motor torque distribution method to consider the energy consumption and slip loss of the motor. First, a torque distribution model is established based on the improved quantum genetic algorithm of the disaster operation. Under NEDC operating conditions, the energy consumption of the in-wheel motor based on the torque distribution method of the improved quantum genetic algorithm is reduced by 11.62 % compared with that of the torque equivalent distribution method and 3.94 % compared with that optimized by the genetic algorithm. Finally, based on the in-wheel motor test bench, the motor torque and the battery SOC curve of the wheel motor under the NEDC condition and UDDS operating conditions are obtained. Experimental results show that the torque distribution method based on the improved quantum genetic algorithm can effectively reduce energy consumption, and it performs better than the ordinary genetic algorithm. Also, the energy consumption optimization effect is the most significant under NEDC conditions, with an energy consumption 11.4 % lower than that of the torque equivalent distribution method and 3.8 % lower than that of the genetic algorithm optimization distribution method.
This is a preview of subscription content,to check access.
Access this article
Chen, H., Yuan, L., Zheng, S. and Lian, X. (2020). Dynamic torque allocation for hub motor driven vehicle based on energy consumption optimization. J. Tsinghua University (Science and Technology) 60, 2, 132–138.
Chen, W., Wang, X., Tan, D., Lin, X., Sun, X. and Xie, Y. (2019). Study on the grey predictive extension control of yaw stability of electric vehicle based on the minimum energy consumption. J. Mechanical Engineering 55, 2, 156–167.
Chen, Y. and Wang, J. (2011). Fast and global optimal energy-efficient control allocation with applications to over-actuated electric ground vehicles. IEEE Trans. Control Systems Technology 20, 5, 1202–1211.
Dizqah, A. M., Lenzo, B., Sorniotti, A., Gruber, P., Fallah, S. and De Smet, J. (2016). A fast and parametric torque distribution strategy for four-wheel-drive energy-efficient electric vehicles. IEEE Trans. Industrial Electronics 63, 7, 4367–4376.
Eto, R., Sakata, K. and Yamakawa, J. (2018). Driving force distribution based on tyre energy for independent wheel-drive vehicle on rough ground. J. Terramechanics, 76, 29–38.
Fan, J. J. and Mao, M. (2007). A Study of driving force distribution strategy for three-axles electric driving vehicle based on economics. Vehicle & Power Technology 159, 1, 52–59.
Gu, C., Liu, H. and Chen, X. (2015). Torque distribution based on efficiency optimization of four wheel independent drive electric vehicle. J. Tongji University (Natural Science) 43, 10, 1500–1556.
Gu, J. (2012). Vehicle Control of Four-wheel Driven Micro Electric Vehicle. Ph. D. Disseration. Tsinghua University. Beijing, China.
Hu, J. S., Yin, D., Hori, Y. and Hu, F. R. (2011). Electric vehicle traction control: A new MTTE methodology. IEEE Industry Applications Magazine 18, 2, 23–31.
Jiang, T., Geng, C., Xue, Q. and Zhang, X. (2019). Torque distribution strategy of FRID EV based on energy consumption optimization. J. Beijing Jiaotong University 43, 5, 102–109.
Koehler, S., Viehl, A., Bringmann, O. and Rosenstiel, W. (2017). Energy-efficiency optimization of torque vectoring control for battery electric vehicles. IEEE Intelligent Transportation Systems Magazine 9, 3, 59–74.
Li, S. and Tang, Y. (2019). Research on torque distribution strategy of dual motor four-drive vehicle based on optimal efficiency. J. Chongqing University of Technology (Natural Science) 33, 7, 12–20.
Lu, D., Ouyang, M., Gu, J. and Li, J. (2012). Torque distribution algorithm for a permanent brushless DC hub motor for four-wheel drive electric vehicles. J. Tsinghua University (Science and Technology) 52, 4, 451–456.
Luo, L., Liu, P., Yang, M., Yang, J. and Yuan, F. (2020). Driving control method for improving economic performance of four-wheel-drive electric buses. Chinese J. Automotive Engineering 10, 2, 107–115.
Maeda, K., Fujimoto, H. and Hori, Y. (2012). Four-wheel driving-force distribution method for instantaneous or split slippery roads for electric vehicle with in-wheel motors. 12th IEEE Int. Workshop on Advanced Motion Control (AMC), Sarajevo, Bosnia and Herzegovina.
Maeda, K., Fujimoto, H. and Hori, Y. (2012). Four-wheel driving-force distribution method based on driving stiffness and slip ratio estimation for electric vehicle with in-wheel motors. IEEE Vehicle Power and Propulsion Conf. (VPPC), Seoul, Korea.
Sun, B., Gao, S., Ma, C. and Li, J. (2018). System power loss optimization of electric vehicle driven by front and rear induction motors. Int. J. Automotive Technology 19, 1, 121–134.
Wu, X. G. and Zheng, D. Y. (2017). Contrastive study on torque distribution of distributed drive electric vehicle under different control methods. Journal of Control Science and Engineering, 2017, 1–12.
Xu, D., Wang, G., Cao, B. and Feng, X. (2012). Study on optimizing torque distribution strategy for independent 4WD electric vehicle. J. Xi’an Jiaotong University 46, 3, 42–46.
Xu, X., Chen, T., Chen, L., Cai, Y. F. and Wang, W. J. (2018). Optimized torque energy-saving allocation for distributed drive electric vehicle. China J. Highway and Transport 31, 5, 183–190.
Yu, Z. P., Zhang, L. J. and Xiong, L. (2005). Optimized torque distribution control to achieve higher fuel economy of 4WD electric vehicle with four in-wheel motors. J. Tongji University 33, 10, 1355–1361.
Zhang, J., (2015). The Longitudinal Dynamic Control of Vehicle Based on Road Identification. Ph. D. Dissertation. Jilin University. Changchun, China.
This work was supported by the National Key Research and Development Program of China (2019YFE0121300).
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
About this article
Cite this article
Wu, S., Li, Y., Guan, Y. et al. Distribution Method of Automotive Torque for Hub Motor Considering Energy Consumption Optimization. Int.J Automot. Technol. 24, 913–928 (2023). https://doi.org/10.1007/s12239-023-0075-9