2008 Special Issue: Toyota Prius HEV neurocontrol and diagnostics

Authors:
Danil V. Prokhorov
Affiliations:
Toyota Technical Center, A division of Toyota Motor Engineering and Manufacturing North America (TEMA), Ann Arbor, MI 48105, United States
Venue:
Neural Networks
Year:
2008

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Abstract

A neural network controller for improved fuel efficiency of the Toyota Prius hybrid electric vehicle is proposed. A new method to detect and mitigate a battery fault is also presented. The approach is based on recurrent neural networks and includes the extended Kalman filter. The proposed approach is quite general and applicable to other control systems.