Abstract
To further improve the efficiency of energy management strategy for heavy-duty Hybrid Electric Vehicle (HEV), taking distributed electric drive heavy-duty Hybrid Electric Vehicle (HEV) as the research object, an energy management strategy combining fuzzy control algorithm and model predictive control (MPC) was proposed, and the length of prediction time domain was optimized by fuzzy algorithm. Simulation results showed that, compared with the fixed time domain model predictive energy management strategy under CHTC-TT working condition, The average time of iteration of the energy management strategy is reduced by about 22.7%, and the fuel consumption per 100 km is reduced by about 2.3%.
| Original language | English |
|---|---|
| Title of host publication | 2023 3rd International Conference on Electrical Engineering and Control Science, IC2ECS 2023 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 1040-1044 |
| Number of pages | 5 |
| ISBN (Electronic) | 9798350382426 |
| DOIs | |
| Publication status | Published - 2023 |
| Event | 3rd International Conference on Electrical Engineering and Control Science, IC2ECS 2023 - Hybrid, Hangzhou, China Duration: 29 Dec 2023 → 31 Dec 2023 |
Publication series
| Name | 2023 3rd International Conference on Electrical Engineering and Control Science, IC2ECS 2023 |
|---|
Conference
| Conference | 3rd International Conference on Electrical Engineering and Control Science, IC2ECS 2023 |
|---|---|
| Country/Territory | China |
| City | Hybrid, Hangzhou |
| Period | 29/12/23 → 31/12/23 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Keywords
- Energy Management Strategy
- RBF
- fuzzy control algorithm
- model predictive control
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