增程式电动汽车增程器多点控制策略优化

doi:10.13229/j.cnki.jdxbgxb20210168

Abstract

Abstract:

Aiming at the multi-objective optimization（MOO） problem of multi-point control strategy for auxiliary power unit（APU） of the range-extended electric vehicle， an energy management control strategy for APU based on MOO results is proposed. Firstly， the vehicle simulation model was established on AVL-Cruise and Matlab-Simulink software， and a MOO model was built with the system energy consumption， emissions and battery capacity attenuation rate as the objective functions based on NSGA-Ⅱ algorithm， the minimum continuous working time of the engine was taken as the optimization variable. In off-line optimization， Pareto optimal solution was obtained under the comprehensive objective. An real-time adaptive fuzzy controller was designed and the minimum continuous working time of the engine was adjusted online. Simulation results show that the proposed strategy can effectively balance the relationship among energy consumption， emissions and battery capacity decay rate， while effectively reducing energy consumption and emissions while maintaining a small battery capacity loss rate.

Key words: vehicle engineering, energy management, auxiliary power unit control strategy, NSGA-Ⅱ algorithm, multi-objective optimization

CLC Number:

U461.8

Han-wu LIU,Yu-long LEI,Xiao-feng YIN,Yao FU,Xing-zhong LI. Multi⁃point control strategy optimization for auxiliary power unit of range⁃extended electric vehicle[J].Journal of Jilin University(Engineering and Technology Edition), 2022, 52(8): 1741-1750.

Figures/Tables 18

Fig.1

Fig.2

Table 1

Parameters of vehicle model"

参数	数值	参数	数值
满载重量/kg	1700	旋转质量换算系数	1.1
电池容量/kW $?$ h	20	总传动比	4.2
轴距/mm	2865	机械效率	0.96
前轴到质心距离/mm	1352	低负荷功率/kW	8
前轴到质心距离/mm	1513	中负荷功率/kW	16
质心高度/mm	500	高负荷功率/kW	28
迎风面积/m²	1.66	电量维持阶段SoC	0.3

Table 1

Fig.3

Fig.4

Fig.5

Fig.6

Fig.7

Fig.8

Fig.9

Table 2

Evaluation function Pareto solution range"

观测指标	$μ i k m i n$	$μ i k m a x$
C_{oil_ele}	0.728	0.755
E_com	0.42	0.70
Q_loss/%	8.5	12.3
I_com	0.65	0.83

Table 2

Table 3

Table 4

Table 5

Table 6

Fig.10

Table 7

Fig.11

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控制策略	C_{oil_ele}	?C_{oil_ele}/%
策略一	0.739	-
策略二	0.735	-14.82
策略三	0.748	33.33
策略四PACS	0.731	-29.63

控制策略	E_com	?E_com/%
策略一	0.52	-
策略二	0.48	-14.29
策略三	0.59	24.87
策略四PACS	0.46	-21.43

控制策略	Q_loss/10^-3	?Q_loss/%
策略一	11.2%	-
策略二	11.9%	18.42
策略三	8.8%	-63.16
策略四PACS	10.4%	-21.11

控制策略	I_com	?I_com/%
策略一	0.72	-
策略二	0.76	23.53
策略三	0.74	11.76
策略四PACS	0.81	53.94

部件	型号
电涡流测功机	CAMA CW-260
程控系统	CAMA FST-4
功率分析仪	YOKOGAWA WT-1800
永磁同步电机	GLMP15L0

Multi⁃point control strategy optimization for auxiliary power unit of range⁃extended electric vehicle

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