Delhi-based Vecmocon Technologies has developed a vehicle intelligence system with critical battery data collection and monitoring, such as cell voltages, temperature, and the current health of the battery.
The company, incubated at FITT-IIT Delhi, with seed support from the Department of Science and Technology, said that it also provides solutions for intelligent vehicles, including keyless entry, preventive and predictive maintenance, user-adaptive algorithms, remote diagnostics, fleet management, and so on.
The system can help in estimating the accurate state of health and state of charge of the battery pack, help fleet operators in their control and facilitate seamless communication. The unavailability of such vehicle intelligent modules for the different components of EVs serves as a roadblock to their efficiency.
It can cater to the entire ecosystem of EVs, such as motor power controllers, battery management systems, vehicle intelligence modules, cloud connectivity, etc., with specialized components for high-performance vehicles.
The patented technology at Technology Readiness Level 9 costs around 20- 22k for the entire kit (Battery Management System – 4-5 k, vehicle Intelligence Module – 6-8 k, fast chargers – 4-5 k, instrument cluster – 2-3 k, motor controller – 4-5 k) and is being used by more than 15 EV Manufacturers as well as Original Equipment Manufacturers (OEMs).
Peeyush Asati, Co-Founder, Vecmocon said, “While others are focused on 2 wheelers, 3 wheelers as a product in the market, we are building the ecosystem for electric vehicles to happen in India at a very faster pace. We develop core components for electric vehicles like Battery Management System, Motor Controller, Vehicle Intelligence Module, Chargers, and the whole of the cloud architecture for Data Analysis, Machine Learning, and Artificial Intelligence,”.
Adarshkumar Balaraman, the other founder, acknowledged DST’s support during the company’s initial stages.
Vecmocon, in a statement, said, that it provides battery packs with all thermal and structural considerations, battery management systems, and Machine Learning (ML) algorithms for battery management design of computationally in-expensive system-local ML algorithms, which run on Rs. 100 micro-controller. It has generated revenue of Rs 5 crore so far.
