Temperature Estimation Using Lumped-Parameter Thermal Network With Piecewise Stator-Housing Modules for Fault-Tolerant Brake Systems in Highly Automated Driving Vehicles

Abstract

With the increased interest in intelligent transportation, the need for fault-tolerant systems has also increased. In this paper, we propose a piecewise stator-housing module (PSM) and construct a lumped-parameter thermal network (LPTN) that can be used in a fault-tolerant system based on the PSM. The proposed LPTN model considers not only radial and axial heat transfer but also tangential heat transfer; therefore, even if only one of the two circuits is running on a fault-tolerant motor (dual winding motor), the coil temperature can be estimated. To verify the proposed model, three winding-type motors are tested with varying current values during normal and fault operations, and the test and analysis results are in good agreement. Additionally, the usefulness of the proposed model is demonstrated by comparing the temperatures of both the conventional and proposed LPTNs in the event of a brake system fault during braking operation in a virtual traffic jam simulation. This simulation demonstrates that temperature estimation of the motor is important for motor design because the brake operation time is dependent on the motor temperature. Furthermore, the system performance or size can be determined by accurately predicting the temperature, even in the event of a fault in the brake system, where the fault-tolerant motor is used, thus keeping the driver safe. The proposed LPTN can be used in brake systems and in other systems that utilize fault-tolerant dual winding motors.