Online State Estimation in Electrified Vehicles Linked to Vehicle Dynamics
Licentiatavhandling, 2015

Electric vehicles have the potential to significantly reduce energy consumption and emissions for personal and commercial road transport and number of electric vehicles is likely to increase in the future due to stricter emission legislations. In order to accelerate market penetration, the competiveness of electric vehicles should increase in comparison to conventional vehicles. Active safety is an area where electric vehicle have a possible advantage over conventional vehicle and that could reduce the number of fatalities and injuries in road traffic accidents. However, the performance of active safety systems today is limited by the knowledge of vehicle state estimates and vehicle parameters, e.g. vehicle speed and the tyre-road friction coefficient. This thesis investigates the potential benefits of using the electric motor as a sensing element to improve state and parameter estimations and thereby also active safety systems. In particular, accurate torque estimation provided by electric propulsion is utilized as an additional source of information. The possibility of using active tyre force excitation for the estimation of the tyre-road friction coefficient is also investigated. The results show that there is a potential to improve the longitudinal and, in some situations, the lateral tyre force estimation using electric motors. However, the estimates are sensitive to errors in the inertial parameters. A method for estimating the vehicle inertial parameters was therefore proposed. The estimate of the vehicle mass converged to within 3% of the measured value for the evaluated test cases. However, the estimation of the longitudinal centre of gravity position and the yaw inertia of the vehicle is sensitive to measurement errors and disturbances. This is mainly due to the weak link between lateral and longitudinal dynamics in normal driving conditions. An alternative method using the seat belt indicators was therefore proposed. This method improves the estimates of these parameters on average when compared to assuming default values. A method to estimate the tyre-road friction coefficient with active tyre force excitation was also proposed. This method enables the estimation of the tyre-road friction coefficient when demanded from an active safety system. Electric motors offer several advantages for active tyre force excitation. The fast response and the ability to apply both positive and negative torque can improve the slip control of the wheels, which is crucial for vehicle stability during the intervention. In summary, the improved wheel torque estimation has the potential to improve the tyre force estimation in both the longitudinal direction directly and in the lateral direction through improved inertial parameter estimation. Furthermore, the electric motor as an actuator provides further opportunities during active tyre force excitation.

electric vehicles

state estimation

vehicle dynamics

parameter estimation

tyre-road friction estimation

active safety

HC3, Hörsalsvägen 14, Chalmers University of Technology
Opponent: MsC. Sven Jansen, TNO Automotive, The Netherlands


Anton Albinsson

Chalmers, Tillämpad mekanik, Fordonsteknik och autonoma system

Identification of tyre characteristics using active force excitation

Dynamics of vehicles on roads and tracks. 24th Symposium of the International-Association-for-Vehicle-System-Dynamics (IAVSD) 2015. Graz, Austria, 17-21 August 2015,; (2015)p. 501-510

Paper i proceeding

Estimation of the inertial parameters of vehicles with electric propulsion

Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering,; Vol. 230(2015)p. 1155-1172

Artikel i vetenskaplig tidskrift

Tire Force Estimation Utilizing Wheel Torque Measurements and Validation in Simulations and Experiments

12th International Symposium on Advanced Vehicle Control (AVEC '14), Tokyo Japan,; (2014)p. 294-299

Paper i proceeding






Technical report - Department of Applied Mechanics, Chalmers University of Technology, Göteborg, Sweden: 2015:18

HC3, Hörsalsvägen 14, Chalmers University of Technology

Opponent: MsC. Sven Jansen, TNO Automotive, The Netherlands