Nonlinear Model Predictive Control for traction motor degradation minimization

Nonlinear Model Predictive Control is used to solve a multi-objective optimal control problem that minimizes degradation while ensuring desired closed loop performance of Permanent Magnet Synchronous Motors used for traction in Electric and Hybrid Electric Vehicles. Unlike industrial motors subjecte...

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Bibliographic Details
Published in2015 54th IEEE Conference on Decision and Control (CDC) pp. 3681 - 3686
Main Authors Samaranayake, Lilantha, Longo, Stefano
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.12.2015
Subjects
Cost function
Degradation
Equivalent circuits
Integrated circuit modeling
Optimal control
Torque
Traction motors
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Summary:Nonlinear Model Predictive Control is used to solve a multi-objective optimal control problem that minimizes degradation while ensuring desired closed loop performance of Permanent Magnet Synchronous Motors used for traction in Electric and Hybrid Electric Vehicles. Unlike industrial motors subjected to constant load demands, motors in electric vehicles have to cater dynamic torque and speed demands depending on the drive cycle. Therefore, it is important to have a control technique which will assure minimum degradation of the motor, while delivering the output similar to or better than conventional controllers. The control scheme is tested for extreme transient conditions that would occur in the practical scenario as well as for standard drive cycles. Performance comparison with the state of the art control scheme reveals that the nonlinear model predictive control scheme results in substantially lower degradation. It effectives saves the motor lifetime by 7.6% for NEDC and 15.7% for ARTEMIS drive cycles.
DOI:10.1109/CDC.2015.7402790