# Abstract
 
This project presents a comprehensive reproduction and optimization study of electric wheel loader speed trajectory optimization for battery lifetime extension, based on the research by Zhang et al. (2022). The study implements and validates a complete system modeling framework incorporating drivetrain dynamics, electric motor characteristics, hydraulic system behavior, and battery aging models. The research develops an innovative Dynamic Programming with Brent Method (DP-BM) optimization algorithm that automatically generates optimal speed trajectories while satisfying physical constraints and operational requirements. Through systematic simulation across nine operational scenarios (combining three distances: 15m, 20m, 25m with three target speeds: 2.0m/s, 2.5m/s, 3.0m/s), the optimized trajectories demonstrate significant improvements over conventional approaches. Key results show that the optimized speed profiles can extend battery lifetime by approximately 4.5% and reduce battery equivalent cycles (FEC) by 21% compared to typical trajectories. The optimization algorithm generates smooth, four-phase speed curves (acceleration-cruise-coast-deceleration) with reduced acceleration slopes, ensuring the electric motor operates more frequently in high-efficiency regions. The study validates all mathematical models including the equivalent circuit battery model with aging-dependent internal resistance, achieving simulation results that closely match the original research findings. This work provides a robust technical foundation for implementing energy-efficient speed control strategies in electric construction machinery, contributing to the advancement of sustainable construction equipment technology and battery management systems.