Adaptive Management of Large Energy Storage Systems for Vehicle Electrification
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Vehicle systems, being either ground/air/water vehicles, require hundreds/thousands of battery cells to meet their power and energy needs. We have been developing comprehensive management solutions of such large-scale batteries with the joint consideration of peak power, operation time, and battery life for vehicle electrification. Specifically, we have investigated (i) the prediction of system power requirement according to its operation contexts, (ii) the monitoring and quantifying of batteries’ real-time status, e.g., state-of-health, and (iii) how to meet such power requirement while considering physical battery properties such as rate-capacity effect, relaxation-effect, thermal behavior, etc. We have evaluated the proposed solutions using both data-driven emulations and prototyping experiments. Our current work focuses on the remote diagnosis of batteries involving on-board system, edge units, and remote service center.
Submitted by Wei Lu
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Vehicle systems, being either ground/air/water vehicles, require hundreds/thousands of battery cells to meet their power and energy needs. We have been developing comprehensive management solutions of such large-scale batteries with the joint consideration of peak power, operation time, and battery life for vehicle electrification. Specifically, we have investigated (i) the prediction of system power requirement according to its operation contexts, (ii) the monitoring and quantifying of batteries’ real-time status, e.g., state-of-health, and (iii) how to meet such power requirement while considering physical battery properties such as rate-capacity effect, relaxation-effect, thermal behavior, etc. We have evaluated the proposed solutions using both data-driven emulations and prototyping experiments. Our current work focuses on the remote diagnosis of batteries involving on-board system, edge units, and remote service center.