PSIM modelling and hall sensors based adaptive control of switched reluctance motor drive for EV applications

SRM is widely used in Electric vehicle applications due to its high starting torque, wide range of variable speed operation and independent phase control. For the work in this paper, we have extended the models in Powersim (PSIM) to include 12/8 Switched Reluctance Motor (SRM) and its drive and have implemented the control parameters with focus on energy efficiency, drive complexity and control characteristics. For enhanced-energy efficiency, regenerative braking is used to recover energy during de-energizing and braking. The hardware implementation has been carried out on a SRM with sensing permanent magnets over the rotor poles for enhanced position accuracy and the drive control has been established on mini6410 using kernel level programming with input from three Hall sensors for complementary positioning and control of phase currents, as shown in block diagram in figure 1. The controller output is used to drive an asymmetric converter to actuate the propulsion operation. Further, the speed tracking and control is done using discrete time PI controller. Our results indicate an efficiency of 88.03 % with rise time of 7 sec for 3000 rpm (3200 rpm rated) with steady state error of 0.22%. The drive has been incorporated for EV application in a purpose built structure for the Shell Eco-Marathon-Asia Challenge, 2017 to validate the performance of our drive design.