학술논문

Real-time electric vehicle mass identification
Document Type
Conference
Source
2013 World Electric Vehicle Symposium and Exhibition (EVS27) Electric Vehicle Symposium and Exhibition (EVS27), 2013 World. :1-6 Nov, 2013
Subject
Power, Energy and Industry Applications
Transportation
Vehicles
Acceleration
Mathematical model
Torque
Batteries
Equations
Real-time systems
modeling & simulation
real-time
mass identification
electric vehicles
Language
Abstract
A technique capable of identifying electric vehicle (EV) mass in real-time has been a topic of research for several years due to the advantages it presents, such as the ability to dramatically improve range estimates, perform more effective torque vectoring for ABS/ESC, track delivery vehicle weight, etc. Some crucial issues in mass identification impede an easy implementation of such an algorithm, however, and this work introduces a simple method to calculate EV mass on-the-fly using standard data available on most CAN buses and therefore without the need of additional sensors. The results presented here are achieved using an eight step technique suitable for accurate mass estimations during wide-open-throttle acceleration events. The algorithm's instantaneous error is less than 10%, and converges to better than 3% absolute accuracy performance with subsequent measurements. A preliminary analysis of trips lacking hard acceleration presented in this paper show an inability to differentiate between loaded and unloaded conditions.