Model predictive control-based dynamic coordinate strategy for hydraulic hub-motor auxiliary system of a heavy commercial vehicle

被引:39
|
作者
Zeng, Xiaohua [1 ]
Li, Guanghan [1 ]
Yin, Guodong [2 ]
Song, Dafeng [1 ]
Li, Sheng [3 ]
Yang, Nannan [1 ]
机构
[1] Jilin Univ, State Key Lab Automot Simulat & Control, Changchun 130025, Jilin, Peoples R China
[2] Southeast Univ, Sch Mech Engn, Nanjing 210096, Jiangsu, Peoples R China
[3] FAW Jiefang Automot CO LTD, Qingdao 266043, Peoples R China
基金
中国国家自然科学基金;
关键词
Hydraulic hub-motor auxiliary system; Dynamic coordinate; Model predictive control; Nonlinear model; Heavy commercial vehicle; REGENERATIVE BRAKING; CONTROL ALLOCATION; PNEUMATIC TIRES; ELECTRIC VEHICLES; SIMULATIONS; FEEDFORWARD;
D O I
10.1016/j.ymssp.2017.08.029
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
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 pro portional-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%. (C) 2017 Elsevier Ltd. All rights reserved.
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页码:97 / 120
页数:24
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