Robust Energy Management Strategy based on the Battery Fault Management for Hydraulic-electric Hybrid Vehicle

被引:0
作者
Kamal, Elkhatib [1 ]
Adouane, Lounis [1 ]
机构
[1] UCA SIGMA UMR CNRS 6602, Inst Pascal IMobS3, Clermont Ferrand, France
来源
ICINCO: PROCEEDINGS OF THE 14TH INTERNATIONAL CONFERENCE ON INFORMATICS IN CONTROL, AUTOMATION AND ROBOTICS - VOL 1 | 2017年
关键词
Artificial Intelligence; Battery Management System; Fuzzy Observer; Hybrid Electric Vehicles; Power Management Strategy; Sensor Faults; Takagi-sugeno Fuzzy Model; ION; PERFORMANCE; SYSTEMS; STATE; MODEL;
D O I
10.5220/0006429700920103
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper deals with a robust energy management strategy, including a battery fault detection and compensation for a hydraulic-electric hybrid vehicle. The overall control and management strategy aims to minimize total energy consumption while ensuring a better battery life. Many power management strategies do not consider battery faults which could accelerate battery aging, decreasing thus its life and could cause also thermal runaway, which may cause fire and battery explosions. Therefore, battery fault tolerant control to guarantee the battery performance is also proposed in this paper. The proposed strategy consists of fuzzy supervisory fault management at the highest level (the second). This level is responsible to detect and compensate the battery faults, generating optimal mode and healthy state of charge set point for first level to prevent overcharge or/and over-discharge. In the first level, an energy management strategy is developed based on neural fuzzy strategy to manage power distribution between electric motor and engine. Then, there are robust fuzzy controllers to regulate the set points of each vehicle subsystems to reach the best operational performance. The Truck-Maker MATLAB simulation results confirm that the proposed architecture can satisfy power requirement for any unknown driving cycles and compensate battery faults effect.
引用
收藏
页码:92 / 103
页数:12
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