Multiple Sensor Fail-Operational Architecture for Electric Vehicle Powertrain Control System

Abstract

With the expanding demand to meet specific safety requirements, a new definition of the architecture at the system level is required to keep the powertrain system still operational after the fault emerge of some sensors. This work proposes a fail-operational architecture by integrating battery management and motor control system, which implements heterogeneous sensor signal reconstruction and model-based signal estimation for redundant signal generation and adopts random forest for signal arbitration. The proposed architecture can reduce the system failure rate and allow a fault-toleration of up to three sensors at any given time without increasing costs. Finally, the proposed architecture was verified by comparing the fault detection performance among three arbitration algorithms in a model in the loop (MIL) platform.