For the research on crucial technologies of range-extended electric vehicle, the first problem to be solved is parametermatching and efficiency optimization for range-extended electric vehicle power and transmission ...
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For the research on crucial technologies of range-extended electric vehicle, the first problem to be solved is parametermatching and efficiency optimization for range-extended electric vehicle power and transmission system. parameter matching and optimization of range-extended electric vehicle power and transmission system are multi-objective optimization problem. Evaluation and analysis of multi-objective optimization problem should be mutually independent and balanced. With the aim of guaranteeing vehicle's comprehensive performance, a parameter matching and optimization method for range-extended electric vehicle power and transmission system is proposed in this paper. First, the house of quality model of range-extended electric vehicle is established to determine weight coefficient of vehicle performance indicator based on market requirements instead of experience. Based on co-simulation control model which is established in Matlab-Simulink and AVL-Cruise, 40 groups of orthogonal tests are performed, and the sensitivity of characteristic parameters is analyzed to explore the coupling law among vehicle performance indicators, so as to clarify the entry point for parameter matching and optimization. The simulation results show that the characteristic parameters not only have a significant influence but also have a coupling effect on the vehicle performance indicators. The analysis of variance shows that there is a limitation in optimal level combination of various factors only by range. Then, particle swarm optimization algorithm is selected to optimize the parameters of range-extended electric vehicle power and transmission system based on sensitivity analysis results obtained above. The study reveals that it is more efficient and reasonable to match the range-extended electric vehicle power and transmission system with a smaller battery capacity and a "medium-sized" auxiliary power unit which can achieve adequate dynamic performance, lower purchase cost, longer
The performance of the vehicle power system for multi-mode hybrid electric vehicle (M-MHEV) can be improved through meticulous parameter matching and optimization. This paper developed the powertrain parameter design ...
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The performance of the vehicle power system for multi-mode hybrid electric vehicle (M-MHEV) can be improved through meticulous parameter matching and optimization. This paper developed the powertrain parameter design and dynamic performance calculation program based on the structure design, parametermatching calculation, and powertrain system selection. A HOQM of M-MHEV is formulated to ascertain the weight coefficient of vehicle performance indicators according to different regional requirements and a parameter matching and optimization method for power system, employing the Particle Swarm optimization (PSO) algorithm, is suggested to assess and harmony the vehicle's performance. Firstly, a house of quality model of M-MHEV is constructed to ascertain the weight coefficient of vehicle performance indicators derived from different regional demands. Additionally, a method is introduced for optimization of power system parameters of M-MHEV based on regional demand, the PSO algorithm is employed to optimize the characteristic parameters. And sensitivity analysis of characteristic parameters is conducted relying on user needs in different regions. The simulation results show that users in the northern and southern regions have different final weight coefficients for vehicle performance indicators and the parameters not only exert a substantial individual influence but also exhibit an interaction effect on the vehicle performance. Finally, a series of comparative simulations, are carried out with two optimizationparameters respectively, the simulation outcomes demonstrate that the solution obtained through optimized design parameters solution could markedly enhance the technical parameters of the vehicle. The efficacy and viability of the proposed method based on user needs in different regions are verified. The conclusion provides a useful reference for differentiated design.
Optimum matching of a target vehicle powertrain was formulated as a nonlinear constrained optimization problem. The dynamic and economic objective functions were respectively set up by maximum grade ability and drivin...
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Optimum matching of a target vehicle powertrain was formulated as a nonlinear constrained optimization problem. The dynamic and economic objective functions were respectively set up by maximum grade ability and driving range. In addition, the simulated annealing genetic algorithm (SAGA) was used to solve the optimum problem. In order to evaluate the effects of the optimized powertrain on vehicle performance, simulation models of the target and optimized vehicles were established in CRUISE software and verified by test results. It is helpful to achieve dynamic performance improvement, energy consumption reduction and driving range increase. (C) 2016 The Authors. Published by Elsevier Ltd.
Optimum matching of a target vehicle powertrain was formulated as a nonlinear constrained optimization problem. The dynamic and economic objective functions were respectively set up by maximum grade ability and drivin...
详细信息
Optimum matching of a target vehicle powertrain was formulated as a nonlinear constrained optimization problem. The dynamic and economic objective functions were respectively set up by maximum grade ability and driving range. In addition, the simulated annealing genetic algorithm (SAGA) was used to solve the optimum problem. In order to evaluate the effects of the optimized powertrain on vehicle performance, simulation models of the target and optimized vehicles were established in CRUISE software and verified by test results. It is helpful to achieve dynamic performance improvement, energy consumption reduction and driving range increase.
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