Longitudinal Vehicle Dynamics Modeling and Parameter Estimation for a Plug-in Hybrid Electric Vehicle

Paper #:
  • 2017-01-1574

Published:
  • 2017-03-28
Abstract:
System identification is an important aspect in model-based control design which is proven to be a cost-effective and time saving approach to improve the performance of hybrid electric vehicles (HEVs). This study focuses on modeling and parameter estimation of the longitudinal vehicle dynamics for a given plug-in HEV (PHEV) with power-split architecture that can be used in successfully developing and evaluating various controllers, such as adaptive cruise control, traction and driveline oscillations control. Particular emphasis is given to the driveline oscillations caused due to low damping present in power- split HEVs by incorporating flexibility in the half shaft and time lag in the tire model. This paper also details a simplified linear driveline model of the above system including transient slip effects to demonstrate the effect of various driveline parameters on the natural frequencies of oscillation. This model captures frequencies which are otherwise absent in commonly used linear driveline models in the literature. Accurate and reliable vehicle dynamics parameters that control the vehicle motion are estimated by acquiring experimental data from longitudinal maneuvers of the PHEV equipped with a vehicle measurement system, CAN bus, GPS and IMU. The simulated model with estimated parameters is analyzed for driveline oscillations and validated by comparing the vehicle states to the data obtained from road tests.
Also in:
  • SAE International Journal of Vehicle Dynamics, Stability, and NVH - V126-10
  • SAE International Journal of Vehicle Dynamics, Stability, and NVH - V126-10EJ
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