Mixed logical dynamical model-based MPC for yaw stability control of distributed drive electric vehicles
Mixed logical dynamical model-based MPC for yaw stability control of distributed drive electric vehicles
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DOI：
10.1016/j.egypro.2019.01.407
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发表时间：
2019-02
期刊：
影响因子：
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通讯作者：
Jian Chen-;Cheng Lin;S. Liang
中科院分区：
文献类型：
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作者：
Jian Chen-;Cheng Lin;S. Liang
基于分布式驱动电动汽车的非线性动力学模型，提出了一种混合模型预测控制器。为了减少预测控制优化过程中的计算量，车辆模型是通过一组分段线性函数近似的魔术轮胎模型。该模型被等效转化为一个混合逻辑动态（MLD）系统，用于设计混合MPC控制器。为了在跟踪参考信号的同时提高系统的能量效率，将输入信号限制在轮内电机的高效率范围内。最后，对不同输入的仿真结果以及闭环和开环系统的比较表明，所提出的混合MPC控制方法能够快速跟踪参考值，并有效地稳定车辆的试验机动。
This paper proposes a hybrid model predictive control (MPC) controller for yaw stability control of distributed drive electric vehicles based on the nonlinear dynamic model. To reduce the computational burden during the optimization process of MPC problem, the vehicle model is formulated by approximating the magic tire model with a set of piecewise linear functions. The dynamic model is equivalently translated into a mixed logical dynamical (MLD) system which is used to design the hybrid MPC controller. To improve the energy efficiency of the system while tracking the reference signals, the input signals are restricted in the high efficiency range of in-wheel motors. Finally, simulation results of different inputs and the comparison of closed-loop and open-loop system indicate the suggested hybrid MPC control method is able to fleetly track the reference and stabilize the vehicle effectively for the test maneuvers.