RACenergy’s retrofit Auto rickshaw
Auto rickshaws are an affordable mode of transportation for people in Asian and African countries. Especially in India, they are equivalent to public transport like bus or train in terms of carrying people from A to B. In this automotive electrification era, many auto giants were offering electric autos as an alternative to existing IC autos but a new auto might not be affordable for all the drivers. RACEnergy’s retrofit auto-rickshaw from Hyderabad might have an affordable conversion alternative for this problem.
RACenergy is a startup by Arun Shreyas and Gautam Maheswaran which began operations in 2018. The startup manufactures EV powertrains and they also work on the infrastructure required for a swapping station. The company has plans for the Electrictrification of the Auto rickshaw category. They are planning to convert the existing IC auto-rickshaws into electric without making the drivers pay for the battery.
RACenergy converts an existing IC auto to electric for the cost of 50-60,000 INR approximately. This is affordable because the cost of the battery pack is not included in this conversion price. Batteries are part of RACenergy’s swapping stations which are available in a network in certain key areas. Drivers of these autos will not exceed the swapping network region and always stay connected. The process of swapping requires only 2 minutes which can save time.
RACenergy claims to be the provider of the lightest swappable battery in the world. With their battery weighing only 10 kgs which is similar to a battery in a scooter. The battery packs can handle extreme temperatures, vibrations and they are also waterproof. Withstanding such parameters is essential for a vehicle because of road conditions and rough usage which an auto-rickshaw might face. The drivers get over-the-air updates and the best battery tech always.
In the backend, the travel data helps to provide an efficient service. This helps in balancing the supply and demand of batteries for battery swapping stations that have different requirements. For example, the demand for batteries is high in the commercial zone when compared to the remote residential area. These analytics will find the area that has a high demand and increase the number of batteries in a particular area.
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