Improved Range Prediction for Electric Vehicles by a Smart Tire Pressure Monitoring System

Abstract

In recent years, the topic vehicle mass estimation has become more and more popular. One of the reasons for this development is the growing spread of electric vehicles. The advantages of a precise vehicle mass estimation for owners of electric vehicles are e.g., a reliable range prediction or the selection of energy efficient routes depending on the current payload and state of charge. This paper presents a novel approach to estimate the vehicle mass by monitoring the tire pressure in combination with a two-stage step detection and a modified Kalman filter. The so-called Smart Tire Pressure Monitoring System offers many chances to enhance energy efficient driving strategies or advanced driver assistance systems. The presented paper shows the results of a large-scale test series of the Smart Tire Pressure Monitoring System. Based on these results, the second part of the paper clarifies the gained improvement of the range prediction by the detected vehicle masses. The analysis of the energy consumption of a Mitsubishi i-MiEV with four own driving cycles highlights the potential for improvement for the range prediction in detail.