Estimation of the Regenerative Braking Process Efficiency in Electric Vehicles

Abstract

Abstract In electric and hybrid vehicles, it is possible to recover energy from the braking process and reuse it to drive the vehicle using the batteries installed on-board. In the conditions of city traffic, the energy dissipated in the braking process constitutes a very large share of the total resistance to vehicle motion. Efficient use of the energy from the braking process enables a significant reduction of fuel and electricity consumption for hybrid and electric vehicles, respectively. This document presents an original method used to estimate the efficiency of the regenerative braking process for real traffic conditions. In the method, the potential amount of energy available in the braking process was determined on the basis of recorded real traffic conditions of the analysed vehicle. The balance of energy entering and leaving the battery was determined using the on-board electric energy flow recorder. Based on the adopted model of the drive system, the efficiency of the regenerative braking process was determined. The paper presents the results of road tests of three electric vehicles, operated in the same traffic conditions, for whom the regenerative braking efficiency was determined in accordance with the proposed model. During the identification of the operating conditions of the vehicles, a global positioning system (GPS) measuring system supported by the original method of phenomenological signal correction was used to reduce the error of the measured vehicle’s altitude. In the paper, the efficiency of the recuperation process was defined as the ratio of the accumulated energy to the energy available from the braking process and determined for the registered route of the tested vehicle. The obtained results allowed to determine the efficiency of the recuperation process for real traffic conditions. They show that the recuperation system efficiency achieves relatively low values for vehicle No. 1, just 21%, while the highest value was achieved for vehicle No. 3, 77%. Distribution of the results can be directly related to the power of electric motors and battery capacities of the analysed vehicles.