One of the constraints that limits regenerative braking in electric vehicles is its inability to regenerate energy under low-speed conditions, due to insufficient back-electromotive force developed in the traction motor. Below a certain speed threshold known as the low-speed cutoff point, energy is extracted from the battery instead of being returned, while overcoming electrical losses in the motor drive system. Although methods implemented to determine dynamic low-speed threshold are reported to result in higher braking efficiencies than fixed point methods, former implementations typically involve dynamic detection of battery current direction, which poses sensing challenges due to factors such as current sensor accuracy, offset, filtering and delays. As an alternative method, this paper proposes a model-based approach to analytically determine the dynamic low-speed cutoff point. Additionally, a loss minimization framework is developed to enhance the amount of energy recovered by achieving a lower value of the cutoff point, thereby extending the braking duration. Simulation studies have been done on a vector-controlled induction motor drive used for a passenger electric car to ascertain braking efficiency improvement. Results indicate that the proposed loss-reducing approach results in the highest efficiency improvement during low torque, high speed operation, when compared to other regions. The magnitude of efficiency improvement depends on system parameters and actual operating conditions of the vehicle. Hence, an example drive cycle has been considered to examine the improvement in practical scenarios. During the region of braking where the motor is operating above its base speed, an overall loss reduction of 30% has been obtained with the low-speed cutoff point lowered from 35 mph to 24 mph. On the other hand, no significant efficiency improvement has been observed in other operating regions.
