Global technology services provider for automotive industry, Tata Elxsi has recently signed a Memorandum of Understanding (MoU) with the Indian Institute of Technology, Guwahati (IIT-G) to jointly work on developing and commercializing state-of-the-art solutions for the electric mobility segment.
The MoU was signed between Parameswar K. Iyer, Officiating Director, IIT Guwahati and Manoj Raghavan, CEO and MD, Tata Elxsi, in the presence of Praveen Kumar, Dept. of Electronics and Electrical Engineering, IIT Guwahati; Anil Radhakrishnan, Director Products, Tata Elxsi and Atul Kulkarni, CTO, Tata Elxsi.
The collaboration aims to bring together researchers and experts for advanced research in material science, digital twins, deep Artificial Intelligence (AI) and Machine Learning (ML) techniques.
Manoj Raghavan “This collaboration will bring together the best minds from Tata Elxsi and IIT Guwahati to envisage and develop future-looking solutions for the fast-evolving space of electric mobility. The fault analysis solution is an excellent example of how industry-academia collaboration can bring together original thinking and application of the latest digital technologies to solve very specific industry needs from operators, OEMs and system suppliers in the transportation industry.”
The collaboration will enable the partners to apply their research capabilities to real-world problems, such as advancing state-of-the-art predictive maintenance.
Parameswar K. Iyer said, “Electric vehicles are being increasingly considered the solution to carbon emissions from the transportation sector, and there is an essential need to create more future-ready solutions in the EV automotive and transportation industry.”
One key area of work under this collaboration will be the digital analysis of electrical signature data for traction motors which underpin electric mobility across segments, including automotive and rail. The solution will provide deep insights for proactive fault prediction, maintenance schedule formulation, and design and manufacturing defects traceability.
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