Power optimization control strategy for dual motor multi-axis drive autonomous vehicles
Dual motor multi-axle drive vehicles are commonly used in heavy-duty transportation scenarios, with high energy consumption and low range during driving. Improving the efficiency of power system operation and improving energy utilization are important ways to solve the problem within a low range. This article takes dual motor multi-axis drive autonomous vehicles as the research object. Besides, it proposes a dual feedback motor torque distribution optimization model and designs a braking torque distribution strategy that meets the optimal braking energy recovery. The dual feedback motor torque distribution optimization model and the braking torque distribution strategy that meets the optimal braking energy recovery are designed. Driving energy consumption and braking energy recovery are used as evaluation indicators to simulate and analyze the C-WTVC cycle and the CHTC-HT cycle conditions. The results show that the driving energy efficiency has been further improved, and the braking energy recovery efficiency has increased by 10%. Therefore, the optimization strategies for driving torque distribution and braking torque distribution designed in this article can both improve energy utilization efficiency, thereby increasing the driving range of the vehicle.
Authors
- Weihua Cheng (ORCID: https://orcid.org/0000-0001-9175-1720)
- Zhentao Tan (ORCID: https://orcid.org/0000-0001-9095-4462)
- Longze Deng
- Chenyu Yi (ORCID: https://orcid.org/0000-0002-5644-7579)
- Haiwei Wang (ORCID: https://orcid.org/0000-0001-6471-801X)
- Xinyun Wang (ORCID: https://orcid.org/0000-0001-7562-2400)
- Peng Xiao (ORCID: https://orcid.org/0000-0002-6401-4116)
Institutions
- Guangzhou Automobile Group (China) (CN)
- Shunde Polytechnic (CN)
- Guangdong Polytechnic Normal University (CN)
Publication Details
- Journal
- Science and Technology for Energy Transition
- Published
- 2025-01-01
- DOI
- https://doi.org/10.2516/stet/2025031
- Primary Topic
- Electric and Hybrid Vehicle Technologies
- Type
- article
- Field-Weighted Citation Impact
- 0.00