Improve Battery Safety for Hybrid Electric Vehicles through Multi-Objective Optimization of Battery Design and Hybridization Level

Electronics ◽  
2019 ◽  
Vol 8 (8) ◽  
pp. 875 ◽  
Author(s):  
Xiaoling Fu ◽  
Qi Zhang ◽  
Jiyun Tang ◽  
Chao Wang

Aiming at problems of large computational complexity and poor reliability, a parameter matching optimization method of a powertrain system of hybrid electric vehicles based on multi-objective optimization is proposed in this paper. First, according to the vehicle basic parameters and performance indicators, the parameter ranges of different components were analyzed and calculated; then, with the weight coefficient method, the multi-objective optimization (MOO) problem of fuel consumption and emissions was transformed into a single-objective optimization problem; finally, the co-simulation of AVL Cruise and Matlab/Simulink was achieved to evaluate the effects of parameter matching through the objective function. The research results show that the proposed parameter matching optimization method for hybrid electric vehicles based on multi-objective optimization can significantly reduce fuel consumption and emissions of a vehicle simultaneously and thus provides an optimized vehicle configuration for energy management strategy research. The method proposed in this paper has a high application value in the optimization design of electric vehicles.


Energies ◽  
2019 ◽  
Vol 12 (13) ◽  
pp. 2563 ◽  
Author(s):  
Wei Li ◽  
Zhiyun Lin ◽  
Kai Cai ◽  
Hanyun Zhou ◽  
Gangfeng Yan

With the increasing popularity of plug-in hybrid electric vehicles (PHEVs), the coordinated charging of PHEVs has become an important issue in power distribution systems. This paper employs a multi-objective optimization model for coordinated charging of PHEVs in the system, in which the problem of valley filling and total cost minimization are both investigated under the system’s technical constraints. To this end, a hierarchical optimal algorithm combining the water-filling-based algorithm with the consensus-based method is proposed to solve the constrained optimization problem. Moreover, a moving horizon approach is adopted to deal with the case where PHEVs arrive and leave randomly. We show that the proposed algorithm not only enhances the stability of the power load but also achieves the global minimization of vehicle owners charging costs, and its implementation is convenient in the multi-level power distribution system integrating the physical power grid with a heterogeneous information network. Numerical simulations are presented to show the desirable performance of the proposed algorithm.


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