Semnan University Press Journal of Modeling in Engineering 2008-4854 17 57 2019 06 22 Optimization and control of hybrid vehicles with considering penalty factors for emission and based on the PSO algorithm Optimization and control of hybrid vehicles with considering penalty factors for emission and based on the PSO algorithm 227 239 3922 10.22075/jme.2019.16666.1651 FA Mohammad Reza Ansari Faculty of Electrical Engineering, University of Shahreza, Isfahan, Iran Iman Hemmat Faculty of Electrical Engineering, University of Shahreza, Isfahan, Iran Journal Article 2018 12 03 This paper presents a new approach to optimizing of the control strategy in parallel hybrid vehicles. By proposing a new objective function and in order to efficient management of the power split between the combustion and electrical motors, fuel consumption and the amount of emissions are minimized with considering the penalty functions. Using the ADVISOR software, as one of the most common software used for a hybrid vehicle, as well as nonlinear equations of these vehicles, a parallel hybrid vehicle in the urban driving cycle of the United States is simulated. In this paper, an extended algorithm based on the Particle Swarm Optimization (PSO) is used. In the proposed PSO algorithm, the coefficients of contraction and the mirror effect of speed are used to increase the efficiency of the method. With the new constraints proposed for the PSO algorithm, the results have been improved. Also, simulation results are compared with the results obtained from the algorithms presented in recent papers. This comparison also shows the efficiency and accuracy of the proposed algorithm in optimizing the control parameters that lead to reduced fuel consumption and emissions from the vehicle. This paper presents a new approach to optimizing of the control strategy in parallel hybrid vehicles. By proposing a new objective function and in order to efficient management of the power split between the combustion and electrical motors, fuel consumption and the amount of emissions are minimized with considering the penalty functions. Using the ADVISOR software, as one of the most common software used for a hybrid vehicle, as well as nonlinear equations of these vehicles, a parallel hybrid vehicle in the urban driving cycle of the United States is simulated. In this paper, an extended algorithm based on the Particle Swarm Optimization (PSO) is used. In the proposed PSO algorithm, the coefficients of contraction and the mirror effect of speed are used to increase the efficiency of the method. With the new constraints proposed for the PSO algorithm, the results have been improved. Also, simulation results are compared with the results obtained from the algorithms presented in recent papers. This comparison also shows the efficiency and accuracy of the proposed algorithm in optimizing the control parameters that lead to reduced fuel consumption and emissions from the vehicle. https://modelling.semnan.ac.ir/article_3922_9b810ab29c9efea652e98b2b9cfd0937.pdf