Energy Management of a 4WD HEV Based on SMPC

Abstract

Abstract: The energy management optimization of 4WD HEV were studied based on the basic principles of SMPC.A Markov model was built to describe the changing processes of the acceleration， so as to predict required torques.The optimization problem was established to minimize fuel consumption while maintaining the balance of battery state of charge （SOC）.This nonlinear optimization problem with finite time horizon was solved with DP algorithm.The proposed control strategy was validated with a software-in-the-loop experiment using dSPACE.The results show that the SMPC may realize the basic energy management of the 4WD HEV and the fuel economy is improved while all power components are working well.Average fuel economy of SMPC is improved by 8.30% comparing with the frozen-time MPC （FTMPC） approach， and is close to the results of the prescient MPC （PMPC） approach.

Key words: four-wheel-drive （4WD） hybrid electric vehicle （HEV）, energy management, stochastic model predictive control （SMPC）, Markov model, dynamic programming （DP）

摘要： 基于随机模型预测控制基本原理，研究了四驱混合动力汽车的能量优化管理。采用马尔可夫模型预测加速度变化过程，通过计算得到混合动力汽车未来需求转矩。在保证电池荷电状态平衡的前提下，以燃油经济性最优为目标，建立混合动力汽车能量管理优化模型。针对建立的非线性优化模型，采用动态规划算法进行有限时域内的滚动求解。将提出的控制策略在dSPACE中进行软件在环仿真试验。研究结果表明，随机模型预测控制策略可以实现四驱混合动力汽车基本的能量管理，可在保证各动力部件良好工作状况的前提下，提升燃油经济性。与基于恒值模型的预测控制策略相比，随机模型预测控制策略下的平均燃油经济性提升了8.30%，优化结果接近有先验知识的预测控制策略。

关键词: 四驱混合动力汽车, 能量管理, 随机模型预测控制, 马尔可夫模型, 动态规划

CLC Number:

U469.72

QIAN Lijun1;JING Hongjuan1;QIU Lihong1，2. Energy Management of a 4WD HEV Based on SMPC[J]. China Mechanical Engineering.

钱立军1;荆红娟1;邱利宏1，2. 基于随机模型预测控制的四驱混合动力汽车能量管理[J]. 中国机械工程.

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