Component Sizing Optimization of 48V Electric Drivetrain for Urban-Sized Zero-Emissions Last-Mile Delivery and Services Vehicles

This research presents an evolutionary algorithm-based optimization framework for determining the best size of primary drivetrain components and the ideal values for the up/down shift speed schedule of a two-speed transmission system applicable to urban freight transports. The optimization loop is merged with a forward-facing vehicle model, scalable component models, and a control algorithm. The NSGA II optimization algorithm is used to optimize the maximum power of the electric motor, the battery capacity, the transmission ratios, and the up/downshift speed schedule of the transmission in order to minimize the energy consumption, the cost of the drivetrain, and the acceleration time.