Commercial vehicle APU control strategy based on neural network identification and Markov chain prediction

doi:10.3969/j.issn.1674-8484.2023.05.009

Abstract

Abstract:

A control strategy was proposed for an electronically-controlled air-processing-unit (APU) based on electromagnetic valve control, with some Simulink system simulation experiment being conducted to improve the fuel economy of commercial-vehicle air-treatment systems. The strategy had three working modes: the basic, the low-pressure, and the high-pressure, based on the identification and prediction methods of engine operating-condition. A vehicle model and an air treatment system model were built by using the Matlab/Simulink. A neural-network pattern recognition and a Markov-chain prediction control model were constructed to identify and classify the engine operating-conditions and predict the required torque percentage. The results show that the electronically controlled APU with this control strategy reduces the power consumption by 480 Wh compared to the mechanically controlled APU under the same initial pressure conditions of air tank in the China World Transient Vehicle Cycle (C-WTVC), with a reduction rate of 34.7%. These results improve fuel economy significantly.

Key words: commercial vehicles, fuel economy, air processing unit (APU), solenoid valve control, control strategy, pattern recognition, Markov chain

CLC Number:

WANG Junqi, LI Yongtao, ZHENG Weiguang, ZHANG Yanhui, CHEN Ziyou, XU Enyong, Li Yufang, WANG Shanchao. Commercial vehicle APU control strategy based on neural network identification and Markov chain prediction[J]. Journal of Automotive Safety and Energy, 2023, 14(5): 600-608.

Figures/Tables 13

References 22

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工况	a / (m·s^-2)			γ (T_req) / %
工况	ave	min	max	ave	max
怠速	0.00	0.00	0.00	11.5	12.0
匀速	-0.04	-1.30	1.18	19.9	27.0
加速	0.78	-0.48	3.50	43.5	82.0
减速	-1.71	-3.82	-0.10	1.5	12.0

工况	a / (m·s^-2)			γ (T_req) / %
工况	ave	min	max	ave	max
怠速	0.00	0.00	0.00	11.5	12.0
匀速	-0.04	-1.30	1.18	19.9	27.0
加速	0.78	-0.48	3.50	43.5	82.0
减速	-1.71	-3.82	-0.10	1.5	12.0

实际类	预测类			识别率 / %
实际类	1	2	3	识别率 / %
1	316	0	4	98.8
2	2	106	0	98.1
3	8	7	558	97.4
正确率 / %	96.9	93.8	99.3	97.9

实际类	预测类			识别率 / %
实际类	1	2	3	识别率 / %
1	316	0	4	98.8
2	2	106	0	98.1
3	8	7	558	97.4
正确率 / %	96.9	93.8	99.3	97.9

车身长度	7.160 m
车身宽度	2.525 m
车身高度	3.940 m
风阻因数	0.527
整车质量	8.8 t
牵引总质量	40.0 t
轮胎规格	12R22.5
主减速器传动比	3.636
发动机最大扭矩	2.4 kNm
发动机最大功率	382 kW
发动机额定转速	1 900 r/min
发动机传动效率	0.99
各档速比	12.1、9.41、7.31、5.71、4.46、3.48、 2.71、2.11、1.64、1.28、1.00、0.28
挡位数量	12
后桥速比	3.636
变速器传动效率	0.98