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Brake Pad Wear Prediction Using Finite Element Techniques
Technical Paper
2021-01-0810
ISSN: 0148-7191, e-ISSN: 2688-3627
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SAE WCX Digital Summit
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English
Abstract
Brakes are the critical component, plays a significant role regards to performance of vehicle. Vehicle safety is also strongly influenced by proper braking operation, which depends on pad to disc contact interface. Pad and disc surfaces are worn out due to continuous braking events, which in turn affects the life of the brake assembly and its performance. This paper presents the brake pad wear prediction of a disc brake assembly. A new and unworn pair of brake pads are considered for the study and tested under different braking scenarios. Wear simulation procedure is formulated based on Rhee’s wear formula and wear calculation model is established based on friction and wear mechanism. The correlation between the wear behavior of a friction material tested under controlled laboratory conditions and finite element method is investigated. Based on the calculated wear, lifespan of the brake pad is also calculated. The predicted life of the pad using inertia brake dynamometer (IBD) is then correlated with the finite element analysis (FEA) results. The variation of wear during a various braking situations are studied and influence of brake pressure, rotor velocity, coefficient of friction, and temperature on the wear is analyzed. As the disc brakes are not sealed, some of the wear particles can become airborne. This paper also presents the simulation procedure to predict the number of airborne particles generated from friction materials in laboratory environments. It is demonstrated that by using the proposed methodology, it is possible to predict the brake pad wear, and the corresponding life span with an accuracy close to the test results. Therefore, this study will be beneficial to design the pad material formulation and to predict its actual life span.
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S, G., Grandhi, S., and S, S., "Brake Pad Wear Prediction Using Finite Element Techniques," SAE Technical Paper 2021-01-0810, 2021, https://doi.org/10.4271/2021-01-0810.Data Sets - Support Documents
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