Abstract

Li-ion batteries are one of the most common rechargeable batteries used in portable electronics, electric vehicles, military operations and aerospace applications such as electric air-crafts, spacecrafts, space rovers, robots, etc. Failure of these batteries could lead to reduced performance, operational impairment and even catastrophic failure, especially in aerospace systems. Monitoring the remaining state of charge (RSOC) of these batteries would greatly improve the reliability of the systems powered by them and will ultimately lengthen their lifetimes. NASA's Mars Global Surveyor spacecraft was lost due to battery failure. Hence, it is very important to find the RSOC of the batteries in making timely decisions. The method to find the state of charge (SOC) of the batteries has been going on since 1938. It started with voltage measurements of the batteries. Since then it kept on improving like Voltage, temperature, and current measurements, Impedance measurements, Coulomb counting, Book-keeping, Kalman filter, EMF, maximum capacity learning algorithm, etc. Determining the RSOC for Li-ion batteries will help the astronauts, scientists, and engineers to make decisions ahead of time before any accidents happen. We will be using MATLAB programing platform to implement an algorithm based on Kalman filters to find the RSOC for Li-ion batteries. Then we will be validating the algorithm using a hardware-in-the-loop battery testbed.

Disciplines

Science and Mathematics Education

Mentor

Bhaskar Saha

Lab site

NASA Ames Research Center (ARC)

Funding Acknowledgement

This material is based upon work supported by the S.D. Bechtel, Jr. Foundation and by the National Science Foundation under Grant No. 0952013. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the S.D. Bechtel, Jr. Foundation or the National Science Foundation.

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URL: http://digitalcommons.calpoly.edu/star/81

 

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