This paper presents a method to estimate the parameters of a longitudinal dynamic model using on-road testing of an electric vehicle. Data acquisition was undertaken on our test vehicle, a Toyota Rav4EV 2012, by collating signals from three different sources: Vehicle Measurement System (VMS) (consisting of wheel force, torque, wheel spin, wheel speed and position sensors), Global Positioning System (GPS) and the Controller Area Network (CAN) of the vehicle. A MATLAB/Simulink based non-linear least square parameter estimation algorithm was used to identify the vehicle parameters including the mass, location of center of gravity, frontal area, coefficient of drag, wheel inertia and road load parameters of the vehicle. A 14 degrees of freedom (DOF), longitudinal dynamics model of the Rav4EV was developed in the MapleSim software using the estimated parameters. The accuracy of the identified parameters and the model was validated by comparing the model output against the experimental data.

Volume Subject Area:
18th International Conference on Advanced Vehicle Technologies
Topics:
Dynamics (Mechanics), Electric vehicles, Roads, Vehicles, Wheels, Algorithms, Center of mass, Computer software, Control equipment, Data acquisition, Degrees of freedom, Drag (Fluid dynamics), Dynamic models, Inertia (Mechanics), Matlab, Measurement systems, Parameter estimation, Particle spin, Rotation, Sensors, Signals, Spin (Aerodynamics), Stress, Testing, Torque
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