Analysis of Battery Life Extension and Benefits for Logistics Delivery Robots Based on Cloud‐Edge Collaboration

Delivery robots in logistics parks commonly suffer from issues such as insufficient battery lifespan, frequent battery replacements, and a mismatch between scheduling and battery management, resulting in elevated operating costs and low operational efficiency. This paper proposes a cloud‐edge collaborative architecture: at the cloud level, an electrochemical degradation model integrating solid electrolyte interphase (SEI) film growth, iron ion leaching, and deep‐discharge corrosion is established; an adaptive weight‐enhanced genetic algorithm is employed to solve the optimization problems of charging scheduling and state thresholds; at the edge level, millisecond‐level real‐time control and offline autonomy are implemented, forming a closed‐loop system of global optimization, edge execution, and terminal feedback. A 12 months controlled experiment was conducted on 80 robots in a logistics park in the Yangtze River Delta. The results show that the average battery lifespan was extended from 1.8 years to 3.5 years, annual comprehensive operating costs were reduced by 55.3%, and the return on investment reached 239.7%, with significant cumulative economic benefits over 5 years. This method suppresses battery aging at the electrochemical degradation mechanism level, providing a practical intelligent solution for energy management in logistics robot fleets.