Deterministic and probabilistic life assessment of a traditional car starter motor based on number of stop/start cycles

Abstract

In this work, a deterministic and probabilistic life assessment for a traditional car starter motor, with the help of timely diagnosing of the starter faults and predicting its remaining useful life, based on number of stop/start cycles, and the corresponding brush and commutator wear, is realized. Furthermore, empirical equations accounting for deterministic and stochastic conditions, which can give the remaining useful life for both the commutator and brushes, are developed by utilizing curve fitting methods for fitting the experimental data, and Monte Carlo method for stochastic calculations. Use of the stochastic one, with the aim of real-time condition monitoring of the health of the starters in a car, can make sense to obtain the most robust and reliable cycles with the consideration of the uncertainties arising from human factors and accuracies of the measurement instruments. Moreover, the proposed empirical models produce life predictions in fair enough agreement with the experienced ones when compared; thus, the brush is concluded to be one of the most likely components to fail during the life of the starter. For the adaptation of the deterministic or stochastic models to other type internal combustion engines, the modification of the proposed models for both components in such a way that it could involve less efforts; for example, few similar experiments to be implemented on the different types of the engines or the directly consideration of the required torque to which the engine is exposed, might be several reasonable solutions that accordingly could save the development time and reduce costs.

Keywords

• life assessment
• starter motor
• automobile
• stop/start cycles
• stochastic analysis