Advances in Transportation Electrification: Energy Management in Dual-Motor Electric Vehicles

Research conducted by Guangxi University and published in the Ieee Transactions On Transportation Electrification has made significant strides in improving energy efficiency in electric vehicles with dual-motor systems. The study, which utilized a novel efficiency-differential reward function (DDPG-DE), demonstrated enhanced energy utilization and overall performance compared to traditional approaches. The findings have far-reaching implications for the transportation sector, where electrification is a critical component of reducing carbon emissions and mitigating climate change.

Key Takeaways:

• The research focused on developing an energy management strategy (EMS) for dual-motor electric vehicles, specifically using deep deterministic policy gradient (DDPG) for optimal energy consumption.
• Two EMSs were proposed: DDPG-AE, an average-efficiency reward function, and DDPG-DE, a novel efficiency-differential reward function designed to exploit front-rear motor efficiency differentials without relying on empirical parameters.
• Under the new European driving cycle (NEDC), DDPG-AE and DDPG-DE reached 91.01% and 93.12% of the optimal benchmark energy consumption, respectively, compared to 87.32% for the dynamic programming (DP) benchmark.
• Under random driving conditions, DDPG-AE and DDPG-DE achieved the benchmark energy consumption of 90.61% and 92.77%, respectively, significantly outperforming traditional approaches.
• The proposed strategy's superior energy efficiency and adaptability were confirmed through extensive simulation and analysis.
• The research highlighted the need for more efficient energy management strategies in dual-motor electric vehicles to overcome the limitations of traditional approaches.

Statistics:

• The DDPG-AE and DDPG-DE algorithms achieved energy consumption rates of 91.01% and 93.12%, respectively, under the NEDC-driving cycle, compared to the DP benchmark's 87.32%.
• Under random driving conditions, DDPG-AE and DDPG-DE achieved energy consumption rates of 90.61% and 92.77%, respectively, significantly outperforming the DP benchmark's 84.12%.
• The simulations were conducted using a range of driving conditions, including the NEDC and random driving conditions, to evaluate the performance of the proposed EMSs.

Sources:

• Ieee Transactions On Transportation Electrification, 2025; 11(5): 12647-12656.
• Ieee Transactions On Transportation Electrification can be contacted at: Ieee-inst Electrical Electronics Engineers Inc, 445 Hoes Lane, Piscataway, NJ 08855-4141, USA.
• Guangxi University, School of Mechanical Engineering, Nanning 530005, People's Republic of China.