Title: On motion resistance estimation and modeling for heterogeneous road vehicles
Overview
- Date:Starts 9 February 2023, 10:00Ends 9 February 2023, 12:00
- Seats available:104
- Location:Room HC2, Hörsalsvägen 14
- Language:English
Mikael Askerdal is a PhD student in the research group Mechatronics, Division of Systems and Control
DIscussion leader is Associate professor Christofer Sundström, Linköping University
Examiner is Professor Jonas Sjöberg
Main supervisor is Professor Jonas Fredriksson
Abstract
Climate change is driving the development of CO2 reducing technologies within the transportation industry. One of the most promising technologies is battery electric vehicles. However, the combination of limited battery capacity, relatively long charging times and few charging stations makes them more vulnerable to conditions when energy consumption is higher than usual compared to vehicles driven by fossil fuel. This thesis focuses on vehicle and environment attributes that create energy-consuming forces resisting the vehicle motion, i.e., the motion resistance and how to model and estimate them.
The method developed in the thesis is based on a separation principle where attributes affecting the motion resistance are separated into vehicle, road and weather characteristics. This enables using vehicle data from heterogeneous vehicles to estimate local road weather conditions. The method is validated using simulations and real vehicle experiments.
The results show that the road and weather conditions can be estimated using data from connected vehicles and energy consumption of heavy-duty vehicle combinations is largely affected by crosswinds. Furthermore, the motion resistance from crosswinds can be characterized by simple models with only a few tuning parameters.
The main conclusions from this work are that road weather conditions including crosswinds need to be accounted for in range estimation algorithms, road weather estimates based on connected vehicle data is a promising technique, and windy days need to be anticipated in advance to avoid potential charging chaos.
Keywords: Range estimation, motion resistance, state estimation, rolling resistance, air resistance, road vehicles, commercial heavy vehicle combinations, passenger cars.
- Full Professor, Systems and Control, Electrical Engineering
