COMBINED POWER MANAGEMENT/DESIGN OPTIMIZATION FOR A FUEL CELL/BATTERY PLUG-IN HYBRID ELECTRIC VEHICLE USING MULTI-OBJECTIVE PARTICLE SWARM OPTIMIZATION

• Published in: International journal of automotive technology pp. 645 - 654
• Main Authors: B. GENG, J. K. MILLS, D. SUN
• Format: Journal Article
• Language: English
• Published: 한국자동차공학회 01.06.2014
• Subjects: 자동차공학
• ISSN: 1229-9138; 1976-3832
• DOI: 10.1007/s12239−014−0067−x

In this paper, the combined power management/design optimization problem is investigated for a fuel cell/Liionbattery PHEV. Formulated as a constrained multi-objective optimization problem (MOP), the combined optimizationproblem simultaneously minimizes the vehicle cost and fuel consumption subject to the vehicle performance requirements. With an emphasis on developing a generic optimization algorithm to find the Pareto front for the synthesized MOP, the Paretobased multi-objective particle swarm optimization (PMOPSO) algorithm is developed, which solely depends on the conceptof Pareto dominance. Three approaches are introduced to the PMOPSO method to address the constrained MOP. They are: (i)by incorporating system constraints in the original objective functions, the constrained MOP is transformed to anunconstrained MOP; (ii) to avoid being trapped in local minima, a disturbance operator with a decaying mutation possibilityis introduced; (iii) to generate a sparsely distributed Pareto front, the concept of crowding distance is utilized to determine theglobal guidance for the particles. Finally, under the Matlab/Simulink software environment, simulation results are presentedto demonstrate the effectiveness of the PMOPSO in the derivation of the true Pareto front. KCI Citation Count: 31