The Future EVs with AI Technology

In recent days, with advent of Artificial Intelligence (AI), a big transformation has started in the automotive industry. Application of AI in EVs has started inducting multiple benefits, including enhanced performance, extended efficiency, better predictive maintenance, additional safety features, improved customer experience…

With the world now being more aware about the carbon emissions exceedingly rapidly to 40 billion metric tons, destroying the environment in all possible aspects, the climate analysts have raised major concern regarding the same. The change in global climate have led the world leaders to urgently minimize the carbon emissions by taking required measures such as being a Net Zero emission by 2050. The first and foremost step to achieve minimum carbon emission targets is by minimizing the use of fossil fuels for power generation, which are the key drivers of global carbon emissions. The use of renewable energy resources for the power generation has increased considerably for the past few years. Similarly, the combustion engine also has a large part to play in increasing carbon emissions hence elevating the air pollution. Consequently, the Electric Vehicles sales have seen a drastic rise to enhance the clean and green energy scenario.

Transition to Electric Vehicles (EVs)

India has seen an exponential growth in Electric vehicle sales as the people have become conscious of the increase in pollution per year, which is surpassing the air quality index in many big as well as small cities which has deteriorated the health of many. To maintain the air quality and to minimize the pollution, there has been a significant boost in EV sales for the past few years. Automobile manufacturing companies have launched wide range of EV models, to accommodate consumers’ interests and cost affordability. It has been estimated that at least 1 in every 5 vehicles sold will be EV. With diverse policies, EV has seen critical growth in the market. The grid integration of E- vehicles have been advantageous for the power system with V2G and G2V applications. Advancements in battery technology and infrastructure have played a crucial role in inclination towards EVs. The development of more efficient and affordable batteries have extended the driving range of electric vehicles, reducing range anxiety for consumers. Additionally, the expansion of charging infrastructure, including public charging stations and home charging solutions, has improved the convenience and accessibility of EVs for consumers. Furthermore, governments and policymakers around the world have shown a strong commitment to promoting electric vehicles as a means to address climate change and reduce emissions.

Electric vehicles, powered by batteries or hydrogen fuel cells, have emerged as a central player in sustainable transport. The widespread adoption of EVs contributes significantly to the reduction of greenhouse gas emissions, as these vehicles produce little to no tailpipe emissions. The automotive industry’s pivot towards electric mobility is not only reducing air pollution but also lessening dependence on fossil fuels.

Types of Electric Vehicles

  • Battery Electric Vehicles (BEVs): These vehicles run solely on electric power stored in high-capacity batteries. They do not have an internal combustion engine and produce zero tailpipe emissions with mile range of 100-300 miles depending on the model.
  • Plug-in Hybrid Electric Vehicles (PHEVs): These vehicles have both an electric motor and an internal combustion engine. They can operate on electric power alone for a limited range before the internal combustion engine kicks in or switch between the two power sources with up to 50 miles range with initial battery charge.

EVs benefits

  • Environmental Benefits: EVs produce lower or zero emissions compared to traditional internal combustion engine vehicles, contributing to reduced air pollution and greenhouse gas emissions.
  • Energy Efficiency: Electric motors are generally more efficient providing smooth operation and stronger acceleartion than internal combustion engines, leading to better energy conversion and consumption.
  • Reduced Fossil Fuel Dependency: EVs can help decrease dependency on traditional fossil fuels, especially when powered by renewable energy sources.
Global Carbon Emissions


  • Range Anxiety: Concerns about the limited driving range of some EVs and the availability of charging infrastructure can contribute to ‘range anxiety’ among potential buyers.
  • Charging Infrastructure: The expansion and availability of charging infrastructure are crucial for the widespread adoption of EVs. Rapid development is ongoing, but challenges persist in some regions.
  • Battery Technology: The cost and performance of batteries are critical factors in the adoption of electric vehicles. Advances in battery technology are essential to improve range, charging times, and overall affordability.

Several automobile companies are actively involved in producing electric vehicles keeping in mind the consumer’s requirements. Tesla, Nissan, Chevrolet, BMW, Mahindra, Hyundai, Honda and Audi are some notable names in the EV market.

Notably, the state of Maharashtra has taken an initiative of starting battery operated vehicles for forest safaris to minimize the pollution in the forest area of Maharashtra, which is a natural habitat for most of the wild animals. The automobile company Mahindra, along with forest department has recently completed a successful pilot project of running E-vehicles in the forest of Tadoba National Park located in Chandrapur district of Maharashtra. This will be India’s first E-vehicle for forest department customized especially for jungle safaris after trials run up to 4 hours when charged for eight hours. If charged for 6-7 hours, it will run up to 3 hours. The trials have successfully completed with minimum to zero carbon emission, less noise, and high efficiency with a Battery Management System (BMS), which manages the health and life of battery with a cycle life of 5 years.

With large number of forest safaris happening daily with increase in carbon emissions and older gypsies, the need of such measure will not only protect the forest ecosystem from pollution but will also contribute to the minimizing the cost of running. Mahindra also declared a similar EV trials for the Sariska Tiger reserve in Alwar, Rajasthan. With this initiative, it is sure that the country is heading slowly but gradually towards decreasing the carbon emissions and also making India clean and green.

Artificial Intelligence Technology for EVs

With ongoing advancements in Artificial Intelligence in EV technology, the Challenges of EVs are expected to be addressed to get an efficient performance. The integration of EVs with AI is a groundbreaking development that is shaping the future of transportation. AI technologies have improved the efficiency and overall user experience.

Here are several ways in which AI is influencing the evolution of EVs:

  • Autonomous Driving: With AI powered systems in EVs, features such as self-driving capabilities, Advanced Driver Assistance Systems (ADAS), and automated parking. These technologies contribute to increased safety reduced accidents, and improved overall traffic management.
  • Range Optimization: AI algorithms analyse driving patterns, traffic conditions, and weather forecasts to optimize the range of electric vehicles. By learning from user behaviour, the AI system can suggest the most energy-efficient routes, predict charging needs, and enhance overall energy management, addressing one of the key concerns known as ‘range anxiety’.
  • Battery Management: Efficient battery management is crucial for the performance and longevity of electric vehicle batteries. AI is employed to monitor and manage battery health, predict battery degradation, and optimize charging and discharging cycles. This helps in extending the lifespan of the battery and maintaining consistent performance over time.
  • Energy Harvesting and Regeneration: AI is utilized to improve energy harvesting and regeneration systems in electric vehicles. By analysing driving conditions and user behaviour, AI can optimize the capture of kinetic energy during braking and deceleration, subsequently converting it into electric energy to recharge the battery.
  • Predictive Maintenance: AI algorithms can predict potential issues with various vehicle components, enabling proactive maintenance. In electric vehicles, this is particularly important for critical components such as the electric motor and power electronics. Predictive maintenance helps prevent unexpected breakdowns and reduces downtime.
  • User Experience and Personalization: AI enhances the overall user experience by personalizing in-car features based on individual preferences and habits. This includes adjusting climate control, entertainment options, and even driving settings. AI-driven personalization creates a more comfortable and tailored driving experience for electric vehicles users.
  • Charging Infrastructure Optimization: AI is applied to optimize the utilization of charging infrastructure. By analysing data on charging station availability, usage patterns, and electricity prices, AI systems can guide electric vehicle users to the most convenient and cost effective charging points.
  • Enhanced Connectivity and Communications: AI facilitates advanced connectivity features, enabling seamless communication between electric vehicles and smart infrastructure. This includes real-time updates on traffic conditions, charging station availability, and over-the-air software updates to improve vehicle functionality.

Artificial Intelligence Technology for Battery Management system

A Battery Management System (BMS) with AI integration represents a sophisticated approach to optimizing the performance, safety, and longevity of batteries, particularly in EVs and renewable energy systems. Here is an overview of AI’s role in BMS improvement:

  • State of Charge (SoC) and State of Health (SoH) Estimation: AI-powered algorithms can accurately estimate the state of charge and state of health of batteries. Machine learning models analyse various parameters such as voltage, current, and temperature to provide real-time and predictive assessments of the battery’s conditions.
  • Predictive Maintenance: AI can predict faults or issues within battery system by analysing historical data and patterns. This enables proactive maintenance, reducing the risk of unexpected failures and improving overall system reliability.
  • Thermal Management: AI algorithms optimize thermal management by predicting temperature variations within the battery pack. This helps regulate heat dissipation and ensures that the battery operates within optimal temperature ranges, enhancing both safety and performance.
  • Balancing Cells: AI-driven BMS can perform intelligent cell balancing, redistributing energy among individual cells to maintain uniform charge levels. This helps prevent overcharging of specific cells, improving overall battery pack efficiency and longevity.
  • Energy Management: AI is employed to optimize charging and discharging cycles based on factors such as user behaviour, energy demand, and grid conditions. This ensures efficient use of stored energy, extends battery life and minimizes degradation.
  • Adaptive Control: AI adapts to changing usage patterns and environmental conditions, continuously optimizing the BMS parameters for different scenarios. This adaptability is particularly crucial in dynamic environments, such as those encountered in EVs.
  • User Behaviour Analysis: AI analyses user behaviour and preferences to create customized charging profiles. This includes predicting optimal charging times, adjusting charge rates based on historical data, and accommodating individual user schedules.
  • Cybersecurity: AI can enhance cybersecurity within the BMS, detecting and responding to potential threats or anomalies in real-time. This is crucial for safeguarding sensitive data and ensuring the secure operation of BMS.
  • Communication with Vehicle Systems: For electric vehicles, AI in the BMS can enable Vehicle-to-Everything (V2X) communication, allowing the battery system to interact with the vehicle, charging infrastructure, and the grid intelligently. It also helps in processes vast amounts of data generated by the BMS, providing insightful analytics and comprehensive reports on battery performance and efficiency.
Mahindra super-eco ranger…


Implementing AI in EVs and BMS is a progressive step towards creating smarter, more efficient, and reliable energy storage solutions. As AI technologies continue to advance, the capabilities of intelligent BMS will likely evolve, contributing to the broader goals of sustainability and energy efficiency. The integration of artificial intelligence into electric vehicles represents a paradigm shift in the automotive industry, ushering in an era of smarter, more efficient, and environmentally friendly transportation. The SOC and SOH have improved remarkably with AI for BMS. As AI technologies continue to advance, we can expect further innovations that will redefine the capabilities and possibilities of Electric Vehicles (EVs).

Reena Meghwal is a PhD scholar in Electrical Department, College of Technology and Engineering.

Vinod Kumar Yadav is currently working as Associate Professor in electrical department, College of technology and engineering, Udaipur, India.

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