An Automated Torque-Following Optimization Method for Energy-Efficient e-Trailer Trucks

As the heavy-duty truck sector accelerates its shift toward carbon neutrality, electrification solutions for semi-trailer trucks are gaining significant attention. One promising solution is the electricity-propelled trailer (e-trailer), which integrates electric drive axles with a traditional engine-powered tractor to form a hybrid powertrain. For flexible and optimized fuel-electric power distribution, this study proposes a torque-following control (TFC) strategy for the e-trailer hybrid system. This strategy dynamically allocates power between the trailer’s motor and the tractor’s engine based on demand characteristics derived from vehicle operating conditions using kernel density estimation and pedal information, with a desktop automated optimization calibration process (AOCP). The TFC strategy offers notable advantages, including compatibility with existing tractor control systems, high flexibility, and enhanced reliability, while ensuring seamless tractor-trailer coordination for improved safety. The AOCP, employing a genetic algorithm and Bayesian optimization, enables rapid development of motor control schemes for various tractor-trailer configurations without extensive real-world testing. Compared to traditional empirical calibration, the AOCP enhances energy efficiency and significantly reduces development time under varying operating conditions. Results from a long-haul truck show that the AOCP method can reduce vehicle energy costs by 1.68% to 21.13%, depending on diverse operating conditions, compared to conventional empirical calibration.