Torsional oscillation-considered mode transition coordinated control for a power-split PHEV based on action dependent heuristic dynamic programming

被引：9

作者：

Wang, Feng ^{[1
,2
]}

Zhang, Jian ^{[1
]}

Xu, Xing ^{[1
]}

Cai, Yingfeng ^{[1
]}

Ni, Shaoyong ^{[3
]}

Que, Hongbo ^{[4
]}

机构：

[1] Jiangsu Univ, Automot Engn Res Inst, 301 Xuefu Rd, Zhenjiang, Jiangsu, Peoples R China

[2] Tianjin Univ, State Key Lab Engines, 92 Weijin Rd, Tianjin, Peoples R China

[3] Chery New Energy Automobile Co Ltd, 226 Huajin South Rd, Wuhu, Anhui, Peoples R China

[4] CRCC Qishuyan Inst Co Ltd, 258 Wuyi Rd, Changzhou, Jiangsu, Peoples R China

来源：

ISA TRANSACTIONS | 2022年 / 126卷

基金：

中国国家自然科学基金; 中国博士后科学基金;

关键词：

Hybrid electric vehicles; Angle -varying mesh stiffness; Suppression of torsional oscillation; Mode transition coordinated control; Engine start-up; ENERGY MANAGEMENT STRATEGY; HYBRID ELECTRIC VEHICLE; ENGINE; VIBRATION; SYSTEM; TORQUE; FUEL;

D O I：

10.1016/j.isatra.2021.07.028

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The mode transition process (MTP) from electric mode to hybrid electric mode (EM-to-HM) will cause the deterioration in occupant comfort of PHEV, to tickle this issue, a torsional oscillation -considered mode transition coordinated control strategy and a novel general evaluation index for MTP are developed in this research, the quality of mode transition and transient torsional oscillation of gears (TTOGs) during MTP are taken into consideration comprehensively. An action dependent heuristic dynamic programming algorithm which takes the vehicle jerk, friction loss and TTOGs as evaluation index is used to optimize the pressure curve of clutch oil and the compensation torque of motor in the entire EM-to-HM process. Finally, the simulation results and hardware-in-the-loop tests show that vehicle jerk and TTOGs are suppressed, and the driving comfort can be improved accordingly. (C) 2021 ISA. Published by Elsevier Ltd. All rights reserved.

引用

页码：597 / 616

页数：20

共 11 条

[11] Convergence and numerical stability of action-dependent heuristic dynamic programming algorithms based on RLS learning for online DLQR optimal control
de Sousa, Guilherme Bonfim
Moraes Rego, Patricia Helena
INTERNATIONAL JOURNAL OF COMPUTATIONAL SCIENCE AND ENGINEERING, 2019, 20 (03) : 317 - 334

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