Design and Multi-Objective Optimization of Key Shifting Components for a Novel Dual-Motor Automatic Transmission in New Energy Heavy-Duty Commercial Vehicles

Current transmissions for new energy heavy-duty commercial vehicles (NE-HDCVs) are mostly modified from traditional mechanical transmissions, suffering from power interruption during gear shifts and compromised energy efficiency. To address these issues, this paper proposes a novel dual-motor automatic transmission capable of power-on shifting, along with an optimized design of its key shifting components. For the planetary gear sets, a design optimization workflow combines feasible candidate generation in KISSsoft with radar-chart-based multi-indicator evaluation to support scheme selection. For wet clutches and brakes, a multi-objective optimization framework integrating a region-decomposition mass function, a BP neural network stress surrogate model, NSGA-II algorithm, and entropy weight decision-making is employed, with mass and maximum principal stress as optimization objectives. Results show that, compared to the initial designs, the optimized clutch and brake schemes achieved reductions of 18.70% and 21.42% in mass, and 73.55% and 42.90% in maximum principal stress, respectively. This study provides a new transmission configuration for NE-HDCVs and offers valuable references for the design optimization of their critical components.