College of Electrical and Information Engineering, Hunan University, Changsha 410082, China.
College of Electrical and Information Engineering, Hunan University, Changsha 410082, China.
ISA Trans. 2018 Jan;72:44-55. doi: 10.1016/j.isatra.2017.10.013. Epub 2017 Nov 10.
Distributed drive electric vehicle(DDEV) has been widely researched recently, its longitudinal stability is a very important research topic. Conventional wheel slip ratio control strategies are usually designed for one special operating mode and the optimal performance cannot be obtained as DDEV works under various operating modes. In this paper, a novel model predictive controller-based multi-model control system (MPC-MMCS) is proposed to solve the longitudinal stability problem of DDEV. Firstly, the operation state of DDEV is summarized as three kinds of typical operating modes. A submodel set is established to accurately represent the state value of the corresponding operating mode. Secondly, the matching degree between the state of actual DDEV and each submodel is analyzed. The matching degree is expressed as the weight coefficient and calculated by a modified recursive Bayes theorem. Thirdly, a nonlinear MPC is designed to achieve the optimal wheel slip ratio for each submodel. The optimal design of MPC is realized by parallel chaos optimization algorithm(PCOA)with computational accuracy and efficiency. Finally, the control output of MPC-MMCS is computed by the weighted output of each MPC to achieve smooth switching between operating modes. The proposed MPC-MMCS is evaluated on eight degrees of freedom(8DOF)DDEV model simulation platform and simulation results of different condition show the benefits of the proposed control system.
分布式驱动电动汽车（DDEV）最近受到广泛研究，其纵向稳定性是一个非常重要的研究课题。传统的车轮滑转率控制策略通常是针对一种特殊的工作模式设计的，而当 DDEV 在各种工作模式下工作时，无法获得最佳性能。本文提出了一种基于模型预测控制器的多模型控制系统（MPC-MMCS），以解决 DDEV 的纵向稳定性问题。首先，总结了 DDEV 的工作状态为三种典型的工作模式。建立了子模型集来准确表示相应工作模式的状态值。其次，分析了实际 DDEV 的状态与每个子模型之间的匹配程度。匹配程度表示为权重系数，并通过修正的递归贝叶斯定理进行计算。然后，为每个子模型设计了非线性 MPC 以实现最佳车轮滑转率。通过并行混沌优化算法（PCOA）实现 MPC 的最优设计，具有计算精度和效率。最后，通过每个 MPC 的加权输出计算 MPC-MMCS 的控制输出，以实现工作模式之间的平滑切换。在 8 自由度（8DOF）DDEV 模型仿真平台上对所提出的 MPC-MMCS 进行了评估，不同条件下的仿真结果表明了所提出控制系统的优势。
