Electric Vehicles (EVs) are reshaping the automotive landscape, offering significant environmental and economic advantages, from reduced emissions to lower maintenance costs. The global transition toward EVs is accelerating, with nearly 14 million new electric cars registered in 2023 alone, bringing the worldwide total to 40 million, as per the International Energy Agency. This surge in adoption highlights a growing consumer preference for sustainable transport solutions, creating an opportunity for manufacturers to harness emerging technologies to meet these evolving demands.

Artificial Intelligence (AI) stands out as a game-changer, poised to drive the next phase of innovation in the EV sector. According to the IBM Institute for Business Value, AI is projected to increase the perceived value of EVs by over 20 per cent. By leveraging AI, manufacturers can refine various aspects of EV performance, efficiency, and user experience, positioning themselves to meet the needs of an increasingly eco-conscious market.

Here are some of the key ways AI is revolutionising EV performance:

Battery optimisation

AI plays a pivotal role in managing the core of any EV—its battery. AI-driven algorithms analyse data from Battery Management Systems (BMS) to predict battery behaviour in diverse operating conditions. This enables better management of charging cycles, battery thermal performance, and overall lifespan. AI can also help optimise charging patterns by considering factors such as grid demand, energy pricing, and user habits. By intelligently scheduling charging sessions during off-peak hours, AI minimises grid stress while maximising battery longevity and performance.

Advanced material discovery:

Beyond battery optimisation, AI can expedite the discovery of new battery materials and chemistries, such as solid-state batteries or advanced lithium-ion variants. Through simulations and data-driven modelling, AI can predict how different materials will perform, accelerating R and D cycles and reducing the time to market for high-performance batteries. This could lead to breakthroughs in energy density, faster charging, and longer battery life.

Predictive and condition-based maintenance:

AI-powered predictive maintenance goes beyond traditional approaches by continuously monitoring vehicle components through an array of sensors. Machine learning algorithms can detect early signs of wear or failure in motors, batteries, and electronic systems, allowing manufacturers to address issues before they lead to breakdowns. This ensures higher reliability, less downtime, and lower maintenance costs for EV owners. Furthermore, condition-based maintenance schedules service only when truly necessary, optimising the vehicle’s uptime and overall operational efficiency.

Energy management and route optimisation:

One of AI’s most promising applications in EVs is the optimisation of energy use. By integrating real-time traffic data, weather conditions, and even road gradients, AI can calculate the most efficient routes for travel, reducing energy consumption and extending vehicle range. For example, AI systems paired with GPS navigation can reroute vehicles to avoid traffic jams, thereby conserving energy. AI can also enhance regenerative braking systems, predicting braking needs and adjusting to maximise energy recovery without compromising safety.

Charging infrastructure optimisation:

As the EV market grows, so does the need for an efficient charging infrastructure. AI can play a crucial role in managing this by analysing patterns of charger usage, peak demand periods, and geographic distribution. With AI’s input, charging networks can be dynamically adjusted to better serve users, reducing wait times and ensuring that charging stations are available where they are most needed.

Autonomous driving:

AI is essential to the development and refinement of autonomous driving technology. By processing vast amounts of sensor data from cameras, radar, and LiDAR, AI enables vehicles to navigate complex environments, making real-time decisions for safe driving. AI’s machine learning capabilities allow autonomous vehicles to continuously improve their performance, adapting to varied road conditions and enhancing overall driving efficiency. This not only improves safety but also optimises energy use by selecting smoother routes and avoiding sudden accelerations or stops.

Personalised user experience and vehicle customisation:

AI helps tailor the driving experience to the individual. By learning a driver’s behaviours and preferences—such as how they accelerate, brake, or manage corners—AI can adjust the vehicle’s performance settings for optimal efficiency and comfort. AI can also optimise interior systems like climate control based on external weather conditions, user preferences, and battery levels. For instance, by managing heating or cooling more efficiently, AI can maintain passenger comfort while minimising the impact on energy consumption.

Smart traffic integration:

In future smart cities, AI could help EVs interact with intelligent traffic management systems. These systems would guide vehicles through the least congested routes, synchronise with traffic signals to reduce stop-start driving, and even predict pedestrian and cyclist movements for safer navigation. This integration could lead to significantly enhanced driving efficiency and safety in urban areas.

AI-assisted manufacturing:

AI’s impact isn’t limited to the vehicles themselves—it can also optimise manufacturing processes. AI can streamline production lines, reduce waste, improve quality control, and predict equipment maintenance needs. This leads to more efficient production of EVs, allowing manufacturers to scale operations while maintaining high standards.

In conclusion, AI’s integration into the EV ecosystem will drive substantial improvements in performance, sustainability, and user experience. As AI continues to evolve, its potential to transform the automotive industry grows, making it a key enabler in the transition towards cleaner, smarter transportation. For manufacturers, embracing AI is not just an option but a necessity in shaping the future of mobility. The road ahead is electric—and AI is steering us toward that future.

The writer is the managing director at SAERA Electric Auto