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| Content Provider | IET Digital Library |
|---|---|
| Author | Xu, Qiwei Luo, Xiaoxiao Jiang, Xiaobiao Zhao, Meng |
| Abstract | In this study, a double fuzzy control strategy for the parallel hybrid electric vehicle (HEV) is proposed, then based on the genetic algorithm (GA) to get better simulation results, and the results are verified by dynamic programming (DP) optimisation. First, the energy management strategy is established by fuzzy control theory. On this basis, considering braking energy recovery, this study designs a double fuzzy vehicle energy control strategy. A simulation analysis of the above two control strategies is carried out in urban dynamometer driving schedule, and the comparison with the work efficiency of the engine and fuel economy performance, respectively, is made; the simulation results show that the double fuzzy control strategy can effectively improve the HEV performance. In order to make rule base more accurate, this study also uses a GA to optimise the fuzzy control rules of the fuzzy controller. Then the DP is used to optimise the energy control strategy and obtain optimal results. The results verified that the design of fuzzy controllers is correct, and the optimised fuzzy control strategy by GA can improve the work efficiency of the engine and fuel consumption. |
| Starting Page | 144 |
| Ending Page | 151 |
| Page Count | 8 |
| ISSN | 20429738 |
| Volume Number | 8 |
| e-ISSN | 20429746 |
| Issue Number | Issue 2, Jun (2018) |
| Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/iet-est/8/2 |
| Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/10.1049/iet-est.2017.0067 |
| Journal | IET Electrical Systems in Transportation |
| Publisher Date | 2018-01-08 |
| Access Restriction | Open |
| Rights Holder | © The Institution of Engineering and Technology |
| Subject Keyword | Braking Energy Recovery Control of Electric Power System Control System Analysis Control System Synthesis Double Fuzzy Vehicle Energy Control Strategy DP Optimisation Dynamic Programming Dynamometers Energy Management Strategy Energy Management System Fuel Economy Fuel Economy Performance Fuzzy Control GA Optimisation Genetic Algorithm HEV Performance Hybrid Electric Vehicle Optimisation Technique Parallel Hybrid Electric Vehicle Simulation Analysis Synthesis Method Transportation Transportation System Control Urban Dynamometer Driving Schedule Work Engine Efficiency |
| Content Type | Text |
| Resource Type | Article |
| Subject | Electrical and Electronic Engineering |
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