Cooling Fan Failure Mode Analysis to Enable Development of Automotive ECU Fan Health Monitoring System

Abstract

Electronic Control Units (ECUs) are widely used in the automotive industry. Recent efforts to enable enhanced and automated driving requires these ECUs to process and execute computationally expensive algorithms. With these developments, the ECUs now have a higher computing power and thus are at a greater risk of overheating that can limit the availability of the essential functionalities in the vehicle. Current passive cooling may no longer be sufficient to mitigate high operating temperatures, and a cooling fan system is preferred for ECU thermal management. The fan health status monitoring is therefore critical to ensure ECU availability and reliability for vehicle operation. Traditionally, fan failures are only detected by comparing the actual fan speed against the commanded speed; however, to enable early degradation detection and prognostics, a more advanced health monitoring system is required. This paper explores fan failure mode analysis and fault injection to enable the development of prognostics. The data collection and fault injection methods were designed to capture both internal (such as motor and ball bearing) and external (such as cracking of the outer casing) failure modes. For example, the fans were exposed to multiple environmental conditions, such as dust, humidity, and heat. These conditions can potentially cause both internal and external failures. The data collection was conducted with the fans running in a standalone setup, being controlled by external equipment to ensure that the electronic input values were known. After running tests for 32 days, sufficient data was collected to enable the degradation modelling. The data will contribute to the development of a predictive algorithm which will estimate the state of health of the fan based on its performance over time. This paper will discuss the failure modes and the data collection aspects.