优化机器人路径以减少电池老化，兼顾循环与日历衰减
Constrained Optimal Planning to Minimize Battery Degradation of Autonomous Mobile Robots
- 用分段线性化方法解决电池老化优化中的双非线性问题
- 案例验证表明路径规划可显著降低电池退化速率
- 适合关注电池寿命的自主移动机器人系统设计者
本文提出一种优化框架，同时考虑自主移动机器人（AMR）电池的循环衰减与日历老化，以在确保任务完成的前提下最小化电池退化。采用矩形法进行分段线性近似，将双线性优化问题转化为可求解形式。通过案例研究验证了该框架在实现最优路径规划、降低电池老化方面的有效性。
原文摘要 · Abstract (English)
This paper proposes an optimization framework that addresses both cycling degradation and calendar aging of batteries for autonomous mobile robot (AMR) to minimize battery degradation while ensuring task completion. A rectangle method of piecewise linear approximation is employed to linearize the bilinear optimization problem. We conduct a case study to validate the efficiency of the proposed framework in achieving an optimal path planning for AMRs while reducing battery aging.
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