Road traffic injuries and deaths are a growing public health concern worldwide, majorly in developing countries. Brake failure constitutes to be one of the primary reasons for accidents. The majority of brake failures are caused due to overheating of the brakes, while wear of lining is another big share-holder. Early detection of such causes can prevent these accidents. This study puts forth a model that can be used for onboard monitoring of drum/disc temperature & lining/pad thickness by taking velocity & road inclination in real-time as inputs. Many quantities are interdependent and vary with respect to time/temperature. Therefore, an incremental approach is used. The model is implemented in the Simulink software. Many standard profiles are also fed to compare results for different terrains and driving conditions. The drivers can also be classified based on their driving behavior. The thermal model can give us an early warning about the brake overheating. This model can be used to study the energy distribution while braking. Researchers and designers can also use this model to study & optimize the brake system.
Brake Health monitoring, Simulink modelling, Prognostics, Brake temperature, Lining wear
Bhandari, V. B. (2010). Design of Machine Elements. Tata McGraw-Hill Education.
Chiaroni, A., & Silveira, Z. (2014, September 30). Thermal Analysis of a Rear Drum Brake for Lightweight Passenger Vehicles. https://doi.org/10.4271/2014-36-0112
Dalimus, Z. (2014). Braking System Modeling and Brake Temperature Response to Repeated Cycle. Mechatronics, Electrical Power, and Vehicular Technology, 5. https://doi.org/10.14203/j.mev.2014.v5.123-128
Fumi, D. E., & Sultan, I. A. (2009). A novel in-vehicle real-time brake-monitoring system. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, 223(6), 793–804. https://doi.org/10.1243/09544070JAUTO996
Jayakrishnan, J., Manghai T.M., A., & Jegadeeshwaran, R. (2020). Real Time Condition Monitoring on Brakes using Machine Learning Techniques. 2020 International Conference on Artificial Intelligence and Signal Processing (AISP), 1–6. https://doi.org/10.1109/AISP48273.2020.9073173
Jazar, R. N. (2017). Vehicle Dynamics: Theory and Application (3rd ed.). Springer International Publishing. https://doi.org/10.1007/978-3-319-53441-1
Jegadeeshwaran, R., & Sugumaran, V. (2015). Health Monitoring of a Hydraulic Brake System Using Nested Dichotomy Classifier – A Machine Learning approach. International Journal of Prognostics and Health Management, 6, 1–10. https://doi.org/10.36001/ijphm.2015.v6i1.2242
Khairnar, H., Phalle, V., & Mantha, S. (2015). Estimation of automotive brake drum-shoe interface friction coefficient under varying conditions of longitudinal forces using Simulink. Friction, 3. https://doi.org/10.1007/s40544-015-0082-6
Khairnar, H., Phalle, V., & Mantha, S. (2016). Comparative Frictional Analysis of Automobile Drum and Disc Brakes. Tribology in Industry, 38, 11–23.
Liang, L., Jian, S., & Xuele, Q. (2005). Study on Vehicle Braking Transient Thermal Field Based on Fast Finite Element Method Simulation (SAE Technical Paper No. 2005-01–3945). SAE International. https://doi.org/10.4271/2005-01-3945
Newcomb, T. P., & Millner, N. (1965). Cooling Rates of Brake Drums and Discs. Proceedings of the Institution of Mechanical Engineers: Automobile Division, 180(1), 191–205. https://doi.org/10.1243/PIME_AUTO_1965_180_019_02
Öztürk, B., Arslan, F., & Öztürk, S. (2013). Effects of Different Kinds of Fibers on Mechanical and Tribological Properties of Brake Friction Materials. Tribology Transactions, 56, 544. https://doi.org/10.1080/10402004.2013.767399
Shafi, U., Safi, A., Shahid, A., Ziauddin, S., & Saleem, M. Q. (2018). Vehicle Remote Health Monitoring and Prognostic Maintenance System. Journal of Advanced Transportation, 2018, 1–10. https://doi.org/10.1155/2018/8061514
Vdovin, A., & Gigan, G. (2020). Aerodynamic and Thermal Modelling of Disc Brakes—Challenges and Limitations. Energies, 13, 203. https://doi.org/10.3390/en13010203
Yan, M., & Jinliang, X. (2018). Prediction Model for Brake-Drum Temperature of Large Trucks on Consecutive Mountain Downgrade Routes Based on Energy Conservation Law. Mathematical Problems in Engineering, 2018, 1–10. https://doi.org/10.1155/2018/4587673
Jafari M., Gauchia A., Zhang K. & Gauchia L. (2015). Simulation and Analysis of the Effect of Real-World Driving Styles in an EV Battery Performance and Aging, IEEE Transactions on Transportation Electrification, 1(4), 391-401. https://doi.org/10.1109/TTE.2015.2483591
Shabbir, W. & Evangelou, S. A. (2014). Efficiency analysis of a continuously variable transmission with linear control for a series hybrid electric vehicle, IFAC Proceedings Volumes, 47(3), 6264–6269. https://doi.org/10.3182/20140824-6-ZA-1003.01770