基于转矩优化分配的分布式电动车辆横摆力矩研究
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摘要
针对分布式电驱动车辆的操纵稳定性问题,设计了一种基于直接横摆力矩的分层控制策略.上层车辆运动控制器采用模糊控制策略,以二自由度模型为参考对象跟随期望状态下的横摆角速度和质心侧偏角,制定出维持车辆稳定行使所需要的纵向力和横摆力矩;下层基于轮胎负荷率最小的目标优化函数,参考电机和路面附着限制,采用加权最小二乘法将转矩合理分配至8个车轮.为与基于规则的平均分配方法进行对比,利用TruckSim和Matlab/Simulink完成了车辆在2种工况下的联合仿真,结果表明:模糊控制策略能对车辆目标状态进行良好跟踪,转矩优化分配方法能更好地跟随参考状态,降低车轮转矩和轮胎负荷率,提升车辆的稳定性.
Aiming at the problem of steering stability of eight-wheel distributed electric drive vehicles, a hierarchical control strategy based on direct yaw moment is designed. The upper layer adopts fuzzy control to design the vehicle motion controller, and the two-degree-of-freedom model is used as a reference object to follow the yaw rate and the side slip angle, which can decide the additional yaw moment needed to maintain stable vehicle performance; the lower layer is based on the optimization function with the lowest tire load rate, with reference to the motor torque and road adhesion limits, which uses WLS method to distribute the longitudinal force and yaw moment to eight wheels, also compared with equally allocation. The strategy is verified by using TruckSim and Matlab/Simulink co-simulation under different working conditions, and the results show that the designed fuzzy control can track the target state well. Compared to the equal allocation, the optimal allocation can better track the reference state, reduce the torque and tire load rate, and improve the handling stability.
Aiming at the problem of steering stability of eight-wheel distributed electric drive vehicles, a hierarchical control strategy based on direct yaw moment is designed. The upper layer adopts fuzzy control to design the vehicle motion controller, and the two-degree-of-freedom model is used as a reference object to follow the yaw rate and the side slip angle, which can decide the additional yaw moment needed to maintain stable vehicle performance; the lower layer is based on the optimization function with the lowest tire load rate, with reference to the motor torque and road adhesion limits, which uses WLS method to distribute the longitudinal force and yaw moment to eight wheels, also compared with equally allocation. The strategy is verified by using TruckSim and Matlab/Simulink co-simulation under different working conditions, and the results show that the designed fuzzy control can track the target state well. Compared to the equal allocation, the optimal allocation can better track the reference state, reduce the torque and tire load rate, and improve the handling stability.
引文
[1] Makoto Kamachi, Kevin Walters. A research of direct yaw-moment control on slippery road for in-wheel motor vehicle[C].// The 22st International Battery, Hybrid and Fuel Cell Electric Vehicle Symposium & Exposition, Yokohama, 2006:2122-2133.
[2] Fujimoto H, Takahashi N, Tsumasaka A, et al. Motion control of electric vehicle based on cornering stiffness estimation with yaw-moment observer[C].// IEEE International Workshop on Advanced Motion Control. IEEE, 2006:206-211.
[3] Mokhiamar O, Abe M. How the four wheels should share forces in an optimum cooperative chassis control[J]. Control Engineering Practice, 2014, 14(3):295-304.
[4] Kim D, Hwang S, Kim H. Vehicle Stability Enhanc-ement of Four-Wheel-Drive Hybrid Electric Vehicle Using Rear Motor Control[J]. IEEE Transactions on Vehicular Technology, 2010, 57(2):727-735.
[5] 陈禹行.布式驱动电动汽车直接横摆力矩控制研究[D]. 长春:吉林大学, 2013.
[6] 褚文博,罗禹贡,赵峰,等.分布式驱动电动汽车驱动转矩协调控制[J]. 汽车工程, 2012, 34(3):185-189.
[7] Osborn R, TaehyunShim. Independent control of all-wheel-drive torque distribution[J]. Vehicle System Dynamics, 2006, 44(7):529-546.
[8] Mokhiamar O, Abe M. How the four wheels should share forces in an optimum cooperative chassis control[J]. Control Engineering Practice, 2014, 14(3):295-304.
[9] Dai Y, Luo Y, Chu W, et al. Optimum tyre force distribution for four-wheel-independent drive electric vehicle with active front steering[J]. International Journal of Vehicle Design, 2014, 65(4):336-359.
[10] Kang J, Yoo J, Yi K. Driving Control Algorithm for Maneuverability, Lateral Stability, and Rollover Prevention of 4WD Electric Vehicles With Indepen-dently Driven Front and Rear Wheels[J]. IEEE Transactions on Vehicular Technology, 2011, 60(7):2987-3001.
[11] 刘明春. 8×8轮毂电机驱动车辆操纵稳定性分析与控制研究[D]. 北京:北京理工大学, 2015.
[12] ManfredMistschke, HenningWallentowitz,米奇克,等.汽车动力学[M]. 北京:清华大学出版社, 2009.
[13] 张晨晨,夏群生,何乐.质心侧偏角对车辆稳定性影响的研究[J]. 汽车工程, 2011, 33(4):277-282.文章编号:1009-4687(2019)01-0023-06
[2] Fujimoto H, Takahashi N, Tsumasaka A, et al. Motion control of electric vehicle based on cornering stiffness estimation with yaw-moment observer[C].// IEEE International Workshop on Advanced Motion Control. IEEE, 2006:206-211.
[3] Mokhiamar O, Abe M. How the four wheels should share forces in an optimum cooperative chassis control[J]. Control Engineering Practice, 2014, 14(3):295-304.
[4] Kim D, Hwang S, Kim H. Vehicle Stability Enhanc-ement of Four-Wheel-Drive Hybrid Electric Vehicle Using Rear Motor Control[J]. IEEE Transactions on Vehicular Technology, 2010, 57(2):727-735.
[5] 陈禹行.布式驱动电动汽车直接横摆力矩控制研究[D]. 长春:吉林大学, 2013.
[6] 褚文博,罗禹贡,赵峰,等.分布式驱动电动汽车驱动转矩协调控制[J]. 汽车工程, 2012, 34(3):185-189.
[7] Osborn R, TaehyunShim. Independent control of all-wheel-drive torque distribution[J]. Vehicle System Dynamics, 2006, 44(7):529-546.
[8] Mokhiamar O, Abe M. How the four wheels should share forces in an optimum cooperative chassis control[J]. Control Engineering Practice, 2014, 14(3):295-304.
[9] Dai Y, Luo Y, Chu W, et al. Optimum tyre force distribution for four-wheel-independent drive electric vehicle with active front steering[J]. International Journal of Vehicle Design, 2014, 65(4):336-359.
[10] Kang J, Yoo J, Yi K. Driving Control Algorithm for Maneuverability, Lateral Stability, and Rollover Prevention of 4WD Electric Vehicles With Indepen-dently Driven Front and Rear Wheels[J]. IEEE Transactions on Vehicular Technology, 2011, 60(7):2987-3001.
[11] 刘明春. 8×8轮毂电机驱动车辆操纵稳定性分析与控制研究[D]. 北京:北京理工大学, 2015.
[12] ManfredMistschke, HenningWallentowitz,米奇克,等.汽车动力学[M]. 北京:清华大学出版社, 2009.
[13] 张晨晨,夏群生,何乐.质心侧偏角对车辆稳定性影响的研究[J]. 汽车工程, 2011, 33(4):277-282.文章编号:1009-4687(2019)01-0023-06