Energy Management Design of Dual-Motor System for Electric Vehicles Using Whale Optimization Algorithm
Dual-motor electric vehicles enhance power performance and overall output capabilities by enabling the real-time control of the torque distribution between the front and rear wheels, thereby improving handling, stability, and safety. In addition to increased energy efficiency, a dual-motor system pr...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-07-01
|
| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/25/14/4317 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850071259006631936 |
|---|---|
| author | Chien-Hsun Wu Chieh-Lin Tsai Jie-Ming Yang |
| author_facet | Chien-Hsun Wu Chieh-Lin Tsai Jie-Ming Yang |
| author_sort | Chien-Hsun Wu |
| collection | DOAJ |
| description | Dual-motor electric vehicles enhance power performance and overall output capabilities by enabling the real-time control of the torque distribution between the front and rear wheels, thereby improving handling, stability, and safety. In addition to increased energy efficiency, a dual-motor system provides redundancy: if one motor fails, the other can still supply partial power, further enhancing driving safety. This study aimed to optimize the energy management strategies of the front- and rear-axis motors, examining the application effects of rule-based control (RBC), global grid search (GGS), and the whale optimization algorithm (WOA). A simulation platform based on MATLAB/Simulink<sup>®</sup> (R2021b, MATLAB, Natick, MA, USA) was constructed and validated through hardware-in-the-loop (HIL) testing to ensure the authenticity and reliability of the simulation results. Detailed tests and analyses of the dual-motor system were conducted under FTP-75 driving cycles. Compared to the RBC strategy, GGS and WOA achieved energy efficiency improvements of 9.1% and 8.9%, respectively, in the pure simulation, and 4.2% and 3.8%, respectively, in the HIL simulation. Compared to the pure RBC strategy, the RBC and GGS strategies incorporating regenerative braking achieved energy efficiency improvements of 26.1% and 29.4%, respectively, in the HIL simulation. Overall, GGS and WOA each present distinct advantages, with WOA emerging as a highly promising alternative energy management strategy. Future research should further explore WOA applications to enhance energy savings in real-world vehicle operations. |
| format | Article |
| id | doaj-art-a80cea3731b24bc8bf332b910c28dac6 |
| institution | DOAJ |
| issn | 1424-8220 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj-art-a80cea3731b24bc8bf332b910c28dac62025-08-20T02:47:21ZengMDPI AGSensors1424-82202025-07-012514431710.3390/s25144317Energy Management Design of Dual-Motor System for Electric Vehicles Using Whale Optimization AlgorithmChien-Hsun Wu0Chieh-Lin Tsai1Jie-Ming Yang2Department of Vehicle Engineering, National Taipei University of Technology, Taipei 10608, TaiwanDepartment of Vehicle Engineering, National Taipei University of Technology, Taipei 10608, TaiwanDepartment of Vehicle Engineering, National Taipei University of Technology, Taipei 10608, TaiwanDual-motor electric vehicles enhance power performance and overall output capabilities by enabling the real-time control of the torque distribution between the front and rear wheels, thereby improving handling, stability, and safety. In addition to increased energy efficiency, a dual-motor system provides redundancy: if one motor fails, the other can still supply partial power, further enhancing driving safety. This study aimed to optimize the energy management strategies of the front- and rear-axis motors, examining the application effects of rule-based control (RBC), global grid search (GGS), and the whale optimization algorithm (WOA). A simulation platform based on MATLAB/Simulink<sup>®</sup> (R2021b, MATLAB, Natick, MA, USA) was constructed and validated through hardware-in-the-loop (HIL) testing to ensure the authenticity and reliability of the simulation results. Detailed tests and analyses of the dual-motor system were conducted under FTP-75 driving cycles. Compared to the RBC strategy, GGS and WOA achieved energy efficiency improvements of 9.1% and 8.9%, respectively, in the pure simulation, and 4.2% and 3.8%, respectively, in the HIL simulation. Compared to the pure RBC strategy, the RBC and GGS strategies incorporating regenerative braking achieved energy efficiency improvements of 26.1% and 29.4%, respectively, in the HIL simulation. Overall, GGS and WOA each present distinct advantages, with WOA emerging as a highly promising alternative energy management strategy. Future research should further explore WOA applications to enhance energy savings in real-world vehicle operations.https://www.mdpi.com/1424-8220/25/14/4317whale optimization algorithmelectric vehicledual-motorglobal grid searchhardware-in-the-loop |
| spellingShingle | Chien-Hsun Wu Chieh-Lin Tsai Jie-Ming Yang Energy Management Design of Dual-Motor System for Electric Vehicles Using Whale Optimization Algorithm Sensors whale optimization algorithm electric vehicle dual-motor global grid search hardware-in-the-loop |
| title | Energy Management Design of Dual-Motor System for Electric Vehicles Using Whale Optimization Algorithm |
| title_full | Energy Management Design of Dual-Motor System for Electric Vehicles Using Whale Optimization Algorithm |
| title_fullStr | Energy Management Design of Dual-Motor System for Electric Vehicles Using Whale Optimization Algorithm |
| title_full_unstemmed | Energy Management Design of Dual-Motor System for Electric Vehicles Using Whale Optimization Algorithm |
| title_short | Energy Management Design of Dual-Motor System for Electric Vehicles Using Whale Optimization Algorithm |
| title_sort | energy management design of dual motor system for electric vehicles using whale optimization algorithm |
| topic | whale optimization algorithm electric vehicle dual-motor global grid search hardware-in-the-loop |
| url | https://www.mdpi.com/1424-8220/25/14/4317 |
| work_keys_str_mv | AT chienhsunwu energymanagementdesignofdualmotorsystemforelectricvehiclesusingwhaleoptimizationalgorithm AT chiehlintsai energymanagementdesignofdualmotorsystemforelectricvehiclesusingwhaleoptimizationalgorithm AT jiemingyang energymanagementdesignofdualmotorsystemforelectricvehiclesusingwhaleoptimizationalgorithm |