Model predictive control-based dynamic coordinate strategy for hydraulic hub-motor auxiliary system of a heavy commercial vehicle
Model predictive control-based dynamic coordinate strategy for hydraulic hub-motor auxiliary system of a heavy commercial vehicle
复制标题
基于模型预测控制的重型商用车液压轮毂电机辅助系统动态协调策略
DOI：
10.1016/j.ymssp.2017.08.029
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发表时间：
2018
影响因子：
8.4
通讯作者：
Yang Nannan
中科院分区：
文献类型：
--
作者：
Zeng Xiaohua;Li Guanghan;Yin Guodong;Song Dafeng;Li Sheng;Yang Nannan
在重型商用车上安装以液压变量泵、液压轮毂马达、液压阀块和液压蓄能器为主要组成部分的液压轮毂马达辅助系统（HHMAS），实现部分时间全轮驱动，可提高重型商用车的动力性和燃油经济性。本文研究了HHMAS在辅助驱动模式下的协调控制问题，该问题的解决是实现HHMAS最大化的关键。为了实现发动机功率在机械和液压路径之间的合理分配，研究了一种基于模型预测控制（MPC）的非线性控制方案。首先，建立了考虑车辆动力学和轮胎滑移特性的HHMAS非线性模型，并对面向整车设计的模型进行了简化。然后，稳态前馈+动态MPC反馈控制器（FMPC）的设计，计算发动机扭矩和液压变量泵排量的控制输入序列。最后，在MATLAB/Simulink和AMESim联合仿真平台和硬件在环实验平台上对该控制器进行了测试，并与现有的比例积分微分控制器和前馈控制器在相同条件下的性能进行了比较。仿真结果表明，所设计的FMPC具有最佳的性能，并且在实时环境下能够保证控制性能。与前馈控制器相比，所设计的FMPC的跟踪控制误差减小了85%，在低摩擦条件下牵引效率性能提高了23%.此外，在重型商用车的普通道路条件下，牵引力可增加13.4- 15.6%。
Equipping a hydraulic hub-motor auxiliary system (HHMAS), which mainly consists of a hydraulic variable pump, a hydraulic hub-motor, a hydraulic valve block and hydraulic accumulators, with part-time all-wheel-drive functions improves the power performance and fuel economy of heavy commercial vehicles. The coordinated control problem that occurs when HHMAS operates in the auxiliary drive mode is addressed in this paper; the solution to this problem is the key to the maximization of HHMAS. To achieve a reasonable distribution of the engine power between mechanical and hydraulic paths, a nonlinear control scheme based on model predictive control (MPC) is investigated. First, a nonlinear model of HHMAS with vehicle dynamics and tire slip characteristics is built, and a controller-design-oriented model is simplified. Then, a steady-state feedforward + dynamic MPC feedback controller (FMPC) is designed to calculate the control input sequence of engine torque and hydraulic variable pump displacement. Finally, the controller is tested in the MATLAB/Simulink and AMESim co-simulation platform and the hardware-in-the-loop experiment platform, and its performance is compared with that of the existing proportional-integral-derivative controller and the feedforward controller under the same conditions. Simulation results show that the designed FMPC has the best performance, and control performance can be guaranteed in a real-time environment. Compared with the tracking control error of the feedforward controller, that of the designed FMPC is decreased by 85% and the traction efficiency performance is improved by 23% under a low-friction-surface condition. Moreover, under common road conditions for heavy commercial vehicles, the traction force can increase up to 13.4–15.6%.