This is a part of the EV  Digital Opportunities series

AI has been making its presence felt in subtle yet important ways in the EV domain. One of the recent emerging trends is that of ‘connected’ vehicles, which utilize AI technologies powered by the relevant data that is fed into them. These vehicles learn by studying the changing user-behavior and the environment around them.

This blog post will discuss the opportunities specific to AI / ML and advancements in the EV industry.

Digital Opportunities in Electric Vehicles – EVIT


AI/ML can be quite beneficial in the following vertices

Battery maintenance

  • Hardware circuits enabled with AI and ML to monitor, predict, Identify and to an extent repair lithium ion battery  defects
  • Research-based on AI to identify  better battery chemistry

Route optimization

  • Routing and navigation solutions based on artificial intelligence and satellite imaging for nearest charging station identification.

Better charging

  • AI application based on customer feedback to identify the infrastructure gaps in the charging networks.
  • AI-based decentralized charging networks with monitoring, maintenance, tracking, and control systems.

Autonomous vehicles

  • AI-assisted autonomous driving for optimal routing considering urban real-time traffic data.
  • AI in Autonomous driving verticals for interaction with the sensory system and the interpretation of the data coming out of sensors and route planning by analyzing the real-time data.


  • AI and ML-enabled smart factories for EV manufacturing to increase operational efficiency.


  • AI in Indian electric scooters – In India, Okinawa has implemented IoT and AI into their flagship electric scooter models, the i-Praise and Ridge+ through the Okinawa Eco App. Through the app, the customers have access to smart functions such as immobilizing their scooter remotely if it is ever stolen. Additionally, the Geo-Fencing feature helps users to set boundaries and can alert them accordingly. The app also tracks driver behavior to give users information about their own driving style which substantially adds to driver security as well as engagement with the vehicle.
  • AI for finding best routes to charging stations – Google announced a new feature for electric vehicle owners that uses artificial intelligence to sort through thousands of public charging stations while finding the best route. Google is using a newly developed routing algorithm that uses a type of math called “graph theory” to present charging stop recommendations to EV owners based on their location, the amount of range left in their vehicle, and the type of plug their vehicles use.
  • AI for detecting defects in Li-ion batteries – PURE EV, an Indian electric 2 wheeler company has developed Artificial Intelligence-driven hardware that automates identification and repair of defects in Lithium-Ion Batteries of Electric Vehicles. PURE EV researchers have designed Artificial Neural Network (ANN)-based algorithms for the system called ‘BaTRics Faraday.’ This system can be used for all the two-wheelers models launched by PURE EV
  • AI for better batteries – Researchers are moving closer to delivering batteries that feature improvements highly sought by engineers and marketers of electric vehicles: batteries that are safer, recharge faster, and are more sustainable than the generation of lithium ion batteries now in use. AI allows researchers to identify the sweet spot between faster charging times and a battery’s expected life.
  • AI to fix gaps in EV charging stations – Artificial Intelligence (AI) has been trained to read user reviews to identify infrastructure gaps in electric vehicle (EV) charging stations. The AI achieved a 91% accuracy and high learning efficiency in parsing the reviews in minutes. The new method can also give insight into consumers’ behavior, enabling rapid policy analysis and making infrastructure management easier for the government and companies.
  • AI for monitoring and scaling EV charging – AutoGrid, the market leader in AI-powered flexibility management software for the energy industry, announced technological compatibility with the FLO® and AddEnergie group, a leading operator of the FLO electric vehicle (EV) charging network and provider of smart charging software and equipment, to provide AutoGrid Flex™ for utility management of smart charging endpoints. The collaboration elevates utilities’ capacity for the continuous measurement, monitoring, and control of EV charging at scale. With AutoGrid Flex’s AI-based analytics and real-time operating data in place, utilities can obtain endpoint-level and network-wide visibility and intelligence on participating AddEnergie-manufactured smart charging stations deployed on the FLO network within their service territories. This provides the ability to manage loads for peak demand shaving, enhance the stability of EV charging loads, and improve grid reliability according to the overall impact of charging network activity.
  • AI for EV manufacturing – Can hailing company Ola announced its partnership with Siemens to build India’s most advanced electric vehicle manufacturing facility in Tamil Nadu. The factory will be AI-Powered with Ola’s proprietary AI Engine and tech stack deeply integrated into every aspect of the manufacturing process. ABB robots will be digitally integrated into Ola’s AI-enabled factory to optimize robot performance, productivity, and product quality.
  • For advanced automated driving – NIO and NVIDIA announced that the automaker has selected the NVIDIA DRIVE Orin™ system-on-a-chip (SoC) for its new generation of electric vehicles, which will offer advanced automated driving capabilities. The EV maker recently revealed its NVIDIA DRIVE Orin-powered supercomputer, dubbed Adam, which will first appear in the ET7 sedan that will ship in China starting in 2022.
  • REVOS provides a smart Mobility Platform for Next-Gen Vehicles. It powers vehicles with an AI-enabled IoT Solution making them the smartest on the road, using vehicle controls. Providing AI-enabled bike-to-cloud solutions. Enabling decentralized charging networks globally. A modular and customizable patent-pending tracking and control system that integrates easily into your vehicles makes them smart and connected.
  • ION Energy is an advanced battery management and intelligence platform focused on building technologies that improve the life and performance of lithium-ion batteries that power electric vehicles and energy storage systems. ION’s software-first, full-stack approach blends advanced electronics, machine learning software and AI with deep domain expertise in energy storage. Their unique electronics platform-as-a-service (PaaS) model is disrupting the business of traditional electronics suppliers by providing full autonomy for manufacturing, transparency in technology and 30-40% savings in cost. ION’s ecosystem enables customers to buy or build custom BMS models.
  • Dox is helping electric vehicle fleet operators reduce inventory costs, battery waste, and sudden failures while optimizing battery maintenance processes by providing a battery predictive analytics platform built using a proprietary machine-learning algorithm. The fleet operator gets a centralized data system where he receives real-time information and machine-driven advice on batteries’ health, services and need for replacements or end-of-life indication.
  • Twaice makes a ‘digital battery twins’ software that enable optimal battery design and precise determination and prediction of battery health along the whole lifecycle in major industries. The company first runs physical simulation models of li-ion batteries to help companies choose the right type and configuration of battery they need for their uses. The simulation can be integrated into any research readily. Then the predictive analysis uses deep battery learning, Machine learning and AI to manage, analyze and optimize the battery operations to increase lifetime and efficiency. The products can also be used individually and independently. This way, Twice provides production, to the product, to aftersale services for Li-ion batteries.

Keywords: Semantic analysis, Image recognition, Unsupervised/supervised learning, Neural networks, Deep learning (ML), AI routing, Remote access, Defect analysis, Monitoring, Real-time data analysis.

This is a part of the EV  Digital Opportunities series

Posts in the series

  1. EVs and Big Data, Analytics, Customized learning
  2. EV and IoT / Cloud Solutions, Sensors, Connectivity, Database
  3. EV and AI / ML, Robotics, Customised learning
  4. EV mobile software applications, Payment gateways, Shared network
  5. EV and VR/AR solutions, Multimedia, Image processing
  6. EV fleet management software, Payment apps, Analytics software
  7. EV BMS software, PCB, PLC, Hardware circuits
  8. EV navigation systems software, Multimedia, Satellite communication, Image processing
  9. EV testing, design and simulation software, Programming, Framework
  10. EV charging software, Payment gateways, PCB, POS, Hardware circuits, Robotics
  11. EV Processes automation Softwares, ERP, Robotics