Research of Multi-objective Parameter Decoupled Optimization Method for Hybrid Electric Vehicle
The energy management strategy (EMS) and the powertrain parameter of hybrid electric vehicles are highly coupled. In the process of hybrid electric vehicle optimization, there is a continuous cycle, which makes it difficult to achieve parameter optimization and find the optimal solution. Aiming at t...
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| Format: | Article |
| Language: | zho |
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Editorial Office of Journal of Mechanical Transmission
2019-06-01
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| Series: | Jixie chuandong |
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| Online Access: | http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2019.06.002 |
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| author | Yiran Zhang Han Zhao Kang Huang Mingming Qiu |
| author_facet | Yiran Zhang Han Zhao Kang Huang Mingming Qiu |
| author_sort | Yiran Zhang |
| collection | DOAJ |
| description | The energy management strategy (EMS) and the powertrain parameter of hybrid electric vehicles are highly coupled. In the process of hybrid electric vehicle optimization, there is a continuous cycle, which makes it difficult to achieve parameter optimization and find the optimal solution. Aiming at this problem, a multi-parameter decouped optimization method is proposed, which adopts hybrid optimization strategy, taking the dynamic targets as constraint conditions and using particle swarm optimization algorithm to optimize powertrain parameter, the Particle swarm optimization (PSO) is used to optimize the energy management strategy and shifting strategy under different parameters. Aiming at a parallel hybrid vehicle, a forward model that includes a fuzzy PID driver is established by using Matlab/Simulink to self-adapt to the changing powertrain configurations. The results show that the hybrid optimization methodology is able to squeeze the potential of the vehicle, compared with the optimization method that simultaneously optimizes the logic gate threshold, the economy performance is enhanced by 4.55% and simultaneously, the energy management strategy and shifting strategy for the HEV under these parameters are obtained. |
| format | Article |
| id | doaj-art-69d6b03ea49b4b7b9c58c2a695c79261 |
| institution | Kabale University |
| issn | 1004-2539 |
| language | zho |
| publishDate | 2019-06-01 |
| publisher | Editorial Office of Journal of Mechanical Transmission |
| record_format | Article |
| series | Jixie chuandong |
| spelling | doaj-art-69d6b03ea49b4b7b9c58c2a695c792612025-01-10T14:00:24ZzhoEditorial Office of Journal of Mechanical TransmissionJixie chuandong1004-25392019-06-014361230641383Research of Multi-objective Parameter Decoupled Optimization Method for Hybrid Electric VehicleYiran ZhangHan ZhaoKang HuangMingming QiuThe energy management strategy (EMS) and the powertrain parameter of hybrid electric vehicles are highly coupled. In the process of hybrid electric vehicle optimization, there is a continuous cycle, which makes it difficult to achieve parameter optimization and find the optimal solution. Aiming at this problem, a multi-parameter decouped optimization method is proposed, which adopts hybrid optimization strategy, taking the dynamic targets as constraint conditions and using particle swarm optimization algorithm to optimize powertrain parameter, the Particle swarm optimization (PSO) is used to optimize the energy management strategy and shifting strategy under different parameters. Aiming at a parallel hybrid vehicle, a forward model that includes a fuzzy PID driver is established by using Matlab/Simulink to self-adapt to the changing powertrain configurations. The results show that the hybrid optimization methodology is able to squeeze the potential of the vehicle, compared with the optimization method that simultaneously optimizes the logic gate threshold, the economy performance is enhanced by 4.55% and simultaneously, the energy management strategy and shifting strategy for the HEV under these parameters are obtained.http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2019.06.002Decoupled optimizationLogic gate energy management strategyPowertrain parameter optimizationParticle swarm optimizationFuzzy PID driver |
| spellingShingle | Yiran Zhang Han Zhao Kang Huang Mingming Qiu Research of Multi-objective Parameter Decoupled Optimization Method for Hybrid Electric Vehicle Jixie chuandong Decoupled optimization Logic gate energy management strategy Powertrain parameter optimization Particle swarm optimization Fuzzy PID driver |
| title | Research of Multi-objective Parameter Decoupled Optimization Method for Hybrid Electric Vehicle |
| title_full | Research of Multi-objective Parameter Decoupled Optimization Method for Hybrid Electric Vehicle |
| title_fullStr | Research of Multi-objective Parameter Decoupled Optimization Method for Hybrid Electric Vehicle |
| title_full_unstemmed | Research of Multi-objective Parameter Decoupled Optimization Method for Hybrid Electric Vehicle |
| title_short | Research of Multi-objective Parameter Decoupled Optimization Method for Hybrid Electric Vehicle |
| title_sort | research of multi objective parameter decoupled optimization method for hybrid electric vehicle |
| topic | Decoupled optimization Logic gate energy management strategy Powertrain parameter optimization Particle swarm optimization Fuzzy PID driver |
| url | http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2019.06.002 |
| work_keys_str_mv | AT yiranzhang researchofmultiobjectiveparameterdecoupledoptimizationmethodforhybridelectricvehicle AT hanzhao researchofmultiobjectiveparameterdecoupledoptimizationmethodforhybridelectricvehicle AT kanghuang researchofmultiobjectiveparameterdecoupledoptimizationmethodforhybridelectricvehicle AT mingmingqiu researchofmultiobjectiveparameterdecoupledoptimizationmethodforhybridelectricvehicle |