DocumentCode :
3283029
Title :
Optimisation of energy flow management in hybrid electric vehicles via genetic algorithms
Author :
Piccolo, Antonio ; Ippolito, Lucio ; Galdi, Vincen Zo ; Vaccaro, Alfredo
Author_Institution :
Dept. of Electron. & Electr. Eng., Salerno Univ., Italy
Volume :
1
fYear :
2001
fDate :
2001
Firstpage :
434
Abstract :
Hybrid electric vehicles powertrain, combining electric motor with an auxiliary power unit, can offer a sensible improvement of the overall vehicle environmental impact achieving at the same time a rational energy employment. The main task of an energy flow management unit is to split the instantaneous vehicle power demand between the internal combustion engine and the electric motor ensuring that the power sources are operated at high efficiency operating points and the related vehicle emissions are minimised. This paper presents an original methodology for the tuning of the characteristic parameters. The proposed methodology identifies, using the genetic algorithm, the value of the energy flow management parameters that minimize the cost function in terms of fuel consumption and emissions. Some interesting simulation results are discussed to prove the validity of the methodology, which contributes to a substantial reduction of the pollutant emissions from hybrid electric vehicles
Keywords :
electric motors; energy management systems; genetic algorithms; internal combustion engines; road vehicles; tuning; cost function; electric motor; energy flow management; genetic algorithms; hybrid electric vehicles; internal combustion engine; optimisation; parameter tuning; pollutant emissions; Cost function; Electric motors; Employment; Energy management; Fuels; Genetic algorithms; Hybrid electric vehicles; Internal combustion engines; Mechanical power transmission; Power demand;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advanced Intelligent Mechatronics, 2001. Proceedings. 2001 IEEE/ASME International Conference on
Conference_Location :
Como
Print_ISBN :
0-7803-6736-7
Type :
conf
DOI :
10.1109/AIM.2001.936493
Filename :
936493
Link To Document :
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