Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/73879
Title: Study of control strategy parameters and component sizing in hybrid electric vehicles using particle swarm optimization
Authors: Wang, J. 
Lu, W.F. 
Keywords: Efficiency
Energy consumption
HEV (hybrid electric vehicle)
Optimization
Simulation
Issue Date: 2012
Source: Wang, J.,Lu, W.F. (2012). Study of control strategy parameters and component sizing in hybrid electric vehicles using particle swarm optimization. 26th Electric Vehicle Symposium 2012, EVS 2012 3 : 1610-1617. ScholarBank@NUS Repository.
Abstract: This paper studies the effect of different control strategy parameters on fuel economy for hybrid electric vehicles. The parameters with significant effect as well as the key component sizing are used in the optimization algorithm to reduce fuel consumption. The optimization algorithm applied in this paper is the PSO algorithm with a proposed approximation approach. The approximation approach is an interpolation method used to generate search-space in the early optimization stage to improve the computational efficiency. Simulations are carried out in Powertrain System Analysis Toolkit (PSAT). The results show that the computational load of the optimization algorithm is greatly reduced for both parallel and series HEVs. This method could be further applied to investigate the optimized parameters for different driving cycles. In this paper, three driving cycles are applied: 2 NEDC, 4 NEDC, and 6 NEDC. The optimized parameters from each of these three driving cycles are used to calculate the fuel economy for all the three driving cycles. Comparing the average and the standard deviation of fuel economy, it is suggested that the parameters optimized from the driving cycle with longer distance provide a better result. This study could be further investigated on the relation between optimized parameters and characteristics of driving cycles to achieve an interactive control strategy parameter advising system in the future.
Source Title: 26th Electric Vehicle Symposium 2012, EVS 2012
URI: http://scholarbank.nus.edu.sg/handle/10635/73879
ISBN: 9781622764211
Appears in Collections:Staff Publications

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