Corrosion Prediction Model for Electrical Components in Automobiles

2024-26-0307

01/16/2024

Features
Event
Symposium on International Automotive Technology
Authors Abstract
Content
Salt Spray Test is being used since 1930’s to accelerate the corrosion testing of materials and to understand the longevity of applied coating. The sample in this kind of test is exposed to a salt mist in a controlled environment and its corrosion resistance is evaluated by measuring the corrosion rate. The Wet-Dry cycle in Salt Spray Test has the ability to simulate the drying and wetting which occurs in real driving scenario, leading to formation of a film of corrosion products which is useful in analyzing the kinetics of electrochemical reaction. Despite the advancement in severity of these tests to understand the atmospheric corrosion phenomena, they still consume time and resources. Secondly, sometimes these kind of tests do not consider into account the effect of Temperature, Humidity and other chemicals in play. Thus, numerical simulation plays a pivotal role in digitalizing the corrosion analysis to a certain extent. It also helps to provide a timesaving, effective, accurate and safe method over traditional testing methods for predicting corrosion behavior and optimizing design and material selection. The aim of this work is to build a simulation prediction system for one of the electrical components of the vehicle. This electrical component qualifies as a critical component for Life Cycle Analysis (LCA) since; it is susceptible to corrosion due to wetting combined with external voltage application. Hence, it becomes imperative to analyze the corrosion hotspots at an early vehicle development stage, based on component shape, size and material configuration. In this work, a corrosion prediction model is developed in COMSOL with right materials, with and without coating, in presence of 5% NaCl solution. A systematic approach has been developed initially for a basic model, which is then applied to the actual component. This study also evaluates different configuration so that this work can be extended to provide corrosion mitigation strategies.
Meta TagsDetails
DOI
https://doi.org/10.4271/2024-26-0307
Pages
6
Citation
Shukrey, S., Yenugu, S., Shah, S., and Bernardi, R., "Corrosion Prediction Model for Electrical Components in Automobiles," SAE Technical Paper 2024-26-0307, 2024, https://doi.org/10.4271/2024-26-0307.
Additional Details
Publisher
Published
Jan 16
Product Code
2024-26-0307
Content Type
Technical Paper
Language
English