Research Projects

One of the largest railway networks is Indian Railways. India has had multiple tragic rail accidents in the past five years. Several hundred people died in the 2023 Balasore train tragedy in Odisha due to a signal malfunction and route miscommunication. The 2021 Gaya train tragedy and associated derailments were caused by mechanical failures, braking failures, and operator incompetence. These fatalities underscore the severity of the issues pertaining to safety and infrastructure. The objective of recent research is to facilitate problem identification, increase brake reliability, and ultimately prevent accidents through automation, tribological evaluation, and mechanical system surveillance. Modern railway braking systems must be safe, reliable, intelligent, energy-efficient, and sustainable. Despite their mechanical durability, conventional braking systems wear out, lose energy as heat, and lack integrated condition monitoring, causing unexpected failures and higher maintenance costs. This proposal suggests adding a Hybrid Triboelectric Nanogenerator (TENG) to railway brake pads and discs for energy collecting and real-time health monitoring. The suggested approach seeks to improve tribological performance through the selection of appropriate material pairs for the brake pad and disk. Aluminium or carbon-based ceramic composites for discs and pads will be developed to guarantee superior wear resistance, thermal stability, and triboelectric compatibility. These materials will be produced via methods such as stir casting, compression molding, and surface modification to enhance mechanical and electrical performance. The TENG technology can convert mechanical energy produced while braking into electrical impulses. These signals can be utilized for energy harvesting and for monitoring critical parameters including frictional force, pad wear, brake disc temperature, and braking engagement time. A hybrid TENG model integrating lateral sliding, contact-separation, and freestanding triboelectric modes will be created to enhance energy output and signal sensitivity during different phases of brake engagement and disengagement. The collected energy will be stored and utilized to energize embedded low-energy IoT modules, facilitating wireless, self-sustaining condition monitoring. A laboratory-scale brake testing apparatus will be developed to recreate real braking circumstances for experimental confirmation. The tribological characterisation (friction, wear) and the performance of the TENG (voltage, current, power density) will be evaluated. The sensor data will undergo processing using IoT-enabled microcontrollers for rule-based diagnostics, eliminating the necessity for machine learning while facilitating predictive maintenance. The project outcomes are expected to yield a self-powered, smart braking system that enhances operational safety, reduces maintenance costs, and supports India’s vision of sustainable and intelligent railways.