Shift scheduling strategy development for parallel hybrid construction vehicles

作     者：LI Tian-yu LIU Hui-ying ZHANG Zhi-wen DING Dao-lin 李天宇;刘惠影;张志文;丁道霖

作者机构：School of Mechanical and Aerospace Engineering Jilin University School of Electronics and Information Engineering Changchun University School of Mechanical and Power Engineering North University of China 

出 版 物：《Journal of Central South University》 (中南大学学报（英文版）)

年 卷 期：2019年第26卷第3期

页      面：587-603页

核心收录：

学科分类：082304[工学-载运工具运用工程] 08[工学] 080204[工学-车辆工程] 0802[工学-机械工程] 0823[工学-交通运输工程] 

基　　金：Project(51805200)supported by the National Natural Science Foundation of China Project(20170520096JH)supported by the Science and Technology Development Plan of Jilin Province,China Project(2016YFC0802900)supported by the National Key R&D Program of China 

主　　题：construction vehicle hybrid electric vehicle shift scheduling strategy shift control neural network 

摘      要：The shift scheduling system of the transmission has an important effect on the dynamic and economic performance of hybrid vehicles. In this work, shift scheduling strategies are developed for parallel hybrid construction vehicles. The effect of power distribution and direction on shift characteristics of the parallel hybrid vehicle with operating loads is evaluated, which must be considered for optimal shift control. A power distribution factor is defined to accurately describe the power distribution and direction in various parallel hybrid systems. This paper proposes a Levenberg-Marquardt algorithm optimized neural network shift scheduling strategy. The methodology contains two objective functions, it is a dynamic combination of a dynamic shift schedule for optimal vehicle acceleration, and an energy-efficient shift schedule for optimal powertrain efficiency. The study is performed on a test bench under typical operating conditions of a wheel loader. The experimental results show that the proposed strategies offer effective and competitive shift performance.