Mobile System Shutdown Prevention via Energy Storage-aware Predictive Control

被引:0
作者
LeSage, Jonathan R. [1 ,2 ]
Longoria, Raul G. [3 ]
机构
[1] MathWorks Inc, Natick, MA 01760 USA
[2] UT Austin, Austin, TX USA
[3] Univ Texas Austin, Dept Mech Engn, Austin, TX 78712 USA
来源
2016 AMERICAN CONTROL CONFERENCE (ACC) | 2016年
关键词
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper presents an energy storage-aware model predictive control approach for online mobile system shutdown prevention that exploits the rate-capacity and recovery dynamic effects of batteries. System shutdown, for these systems such as ground robotics, commonly occurs as a result of transient loads that result in the battery voltage crossing a shutdown voltage threshold in the protective circuitry. The proposed control methodology optimizes the vehicle drive command by incorporating battery shutdown constraints and battery dynamic effects into a model predictive control quadratic program optimization. The proposed model predictive control scheme is shown to extend mobile system run-time and total distance through Monte Carlo simulation and experimental studies of a small unmanned ground vehicle.
引用
收藏
页码:6815 / 6820
页数:6
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