Neuro-Fuzzy System for Energy Management of Conventional Autonomous Vehicles

被引：12

作者：

Duong Phan ^{[1
,2
]}

Bab-Hadiashar, Alireza ^{[1
]}

Hoseinnezhad, Reza ^{[1
]}

Jazar, Reza N. ^{[1
]}

Date, Abhijit ^{[1
]}

Jamali, Ali ^{[3
]}

Dinh Ba Pham ^{[2
]}

Khayyam, Hamid ^{[1
]}

机构：

[1] RMIT Univ, Sch Engn, Melbourne, Vic 3083, Australia

[2] Vietnam Maritime Univ, Inst Engn Mech, Div Mechatron, Haiphong 180000, Vietnam

[3] Univ Guilan, Fac Mech Engn, Rasht 4199613776, Gilan Province, Iran

来源：

ENERGIES | 2020年 / 13卷 / 07期

关键词：

autonomous vehicles; intelligent energy management system; neuro-fuzzy; IDENTIFICATION; STRATEGIES;

D O I：

10.3390/en13071745

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

This paper investigates the energy management system (EMS) of a conventional autonomous vehicle, with a view to enhance its powertrain efficiency. The designed EMS includes two neuro-fuzzy (NF) systems to produce the optimal torque of the engine. This control system uses the dynamic road power demand of the autonomous vehicle as an input, and a PID controller to regulate the air mass flow rate into the cylinder by changing the throttle angle. Two NF systems were trained by the Grid Partition (GP) and the Subtractive Clustering (SC) methods. The simulation results show that the proposed EMS can reduce the fuel consumption of the vehicle by 6.69 and 6.351/100 km using the SC and the GP, respectively. In addition, the EMS based on NF trained by GP and NF trained by SC can reduce the fuel consumption of the vehicle by 11.8% and 7.08% compared with the case without the controller, respectively.

引用

页数：16

共 33 条

[1]

[Anonymous], 2013, PATTERN RECOGN, DOI DOI 10.1007/978-1-4757-0450-1

[2]

Babuska R., 2003, Annual Reviews in Control, V27, P73, DOI 10.1016/S1367-5788(03)00009-9

[3]

Chiu S, 1994, Journal of Intelligent & Fuzzy Systems, V2, P267, DOI DOI 10.3233/IFS-1994-2306

[4] Automotive Powertrain Modeling for Control [J].

Cho, D. ;

Hedrick, J. K. .

JOURNAL OF DYNAMIC SYSTEMS MEASUREMENT AND CONTROL-TRANSACTIONS OF THE ASME, 1989, 111 (04) :568-576

[5] Intelligent energy management system for conventional autonomous vehicles [J].

Duong Phan ;

Bab-Hadiashar, Alireza ;

Lai, Chow Yin ;

Crawford, Bryn ;

Hoseinnezhad, Reza ;

Jazar, Reza N. ;

Khayyam, Hamid .

ENERGY, 2020, 191

[6]

Heywood JB, 1988, INTERNAL COMBUSTION

[7]

Jang J.S.R., 1997, IEEE Transactions on Automatic Control, DOI DOI 10.1109/TAC.1997.633847

[8] ANFIS - ADAPTIVE-NETWORK-BASED FUZZY INFERENCE SYSTEM [J].

JANG, JSR .

IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS, 1993, 23 (03) :665-685

[9]

Jazar R.N., 2019, NONLINEAR APPROACHES

[10]

Khayyam H, 2018, NONLINEAR APPROACHES, P345

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