Abstract
Regenerative braking control technology of electric vehicle plays a vital role in automotive energy-saving and environmental protection. Actually, there are two important aspects included in regenerative braking control. First and foremost is to maintain the vehicle safety during the braking process, and secondly is to maximize the energy recovery and minimize the energy consumption as far as possible. This paper proposes a regenerative braking control strategy to meet the above two aspects. In this research, the electric vehicle is assumed to keep straight line driving with a driver. First, according to the desired braking torques of the driver during braking process, the brake torque on front and rear axle respectively are allocated based on the tire load ratio, which makes sure that maximizing the use of tire adhesion during deceleration. Second, in order to deal with multi-objections and constraints for maximizing the energy recovery and minimizing the energy consumption, an model predictive controller is designed to distribute the brake torque between the hydraulic brake mode and the electric motor brake mode. In the end, the effectiveness of the proposed strategy is verified through the simulations of the electric vehicle model with four individually driven in-wheel motors based on Matlab/Simulink and AMESim software.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 35th Chinese Control Conference, CCC 2016 |
| Editors | Jie Chen, Qianchuan Zhao, Jie Chen |
| Publisher | IEEE Computer Society |
| Pages | 8671-8676 |
| Number of pages | 6 |
| ISBN (Electronic) | 9789881563910 |
| DOIs | |
| State | Published - 26 Aug 2016 |
| Externally published | Yes |
| Event | 35th Chinese Control Conference, CCC 2016 - Chengdu, China Duration: 27 Jul 2016 → 29 Jul 2016 |
Publication series
| Name | Chinese Control Conference, CCC |
|---|---|
| Volume | 2016-August |
| ISSN (Print) | 1934-1768 |
| ISSN (Electronic) | 2161-2927 |
Conference
| Conference | 35th Chinese Control Conference, CCC 2016 |
|---|---|
| Country/Territory | China |
| City | Chengdu |
| Period | 27/07/16 → 29/07/16 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
-
SDG 7 Affordable and Clean Energy
Keywords
- electric vehicle
- model predictive control
- optimal control
- regenerative braking
Fingerprint
Dive into the research topics of 'A regenerative braking control strategy for electric vehicle with four in-wheel motors'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver