The critical need for traction electric machine (EM) control in electric vehicle powertrains arises from its pivotal role in optimizing efficiency, performance, and overall driving experience. The main purpose of the EM control system is to precisely manage the flow of electrical power to the EM, ensuring seamless acceleration, deceleration, and torque distribution. A robust EM control algorithm helps electric vehicles to achieve high energy efficiency, extended battery range and enhanced regenerative braking capabilities, ultimately contributing to the widespread adoption and sustainability of electric transportation. This research paper presents the sliding Mode Control (SMC) technique-based traction machine control, supported by Sliding Mode Observer(SMO) for load torque estimation. The results show that SMC with SMO achieves better performance in tracking reference speed and torque profiles. The comparison was made with a conventional sliding mode torque observer. Results show that the upgraded sliding mode torque observer tracks the reference torque trajectory with 0.9% torque ripple whereas the conventional sliding mode observer has 8% torque ripple. It shows that the upgraded observer has 10 times reduced ripples in the torque control loop as compared to the conventional observer. The proposed controller-observer pair is also tested on hardware setup, where the vehicle transmission is replaced by an electrical load. Both controller and observer are implemented on Lab VIEW and the interface of LabVIEW and EM drive is established by ARM Cortex M4 micro-controller. Hardware results show the 0.5% ripple in the speed profile.


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    Title :

    Load Torque Estimation for Efficient Operation of PMSM-Based Electrified Powertrain


    Contributors:


    Publication date :

    2024-06-19


    Size :

    6022055 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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