How companies are building and leveraging AI to enhance innovation and efficiency in the battery value chain

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Batteries, being the largest cost centre in EVs, have always attracted innovation from capable founders excited to drive electrification. AI and Generative models specifically provide a novel lens to look at possible disruptions to the value chain. After looking at hundreds of global and domestic players and speaking to investors and founders in the space, we have identified a few major push areas that we think will dictate how batteries are built, improved upon and maintained in the coming decade, with a focus on India and its unique nuances.

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What's happening already

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Battery Supply Chain

The supply chain for EV batteries faces significant challenges, making it a prime area for AI-led disruption. Startups like Earth AI, a San Francisco-based company with $18 million in funding, are enabling the discovery of untapped critical metal deposits at half the cost in a fraction of the time. VerAI, with $15 million in Series A funding, leverages AI to enhance the success rates of mineral exploration to drive global decarbonization and electrification. KoBold Metals, backed by over $400 million from investors including a16z and Mitsubishi, uses proprietary AI to identify essential battery metals such as nickel, copper, cobalt, and lithium. Meanwhile, Circulor, a London-based Series B startup with $45 million in funding, uses AI to track materials, emissions, and compliance for sustainable and responsible sourcing. In India, the potential for growth in this sector is huge, given the nascent stages of its domestic battery manufacturing capabilities.

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Novel Chemistries

The discovery of novel battery chemistries specifically is greatly advanced by Generative AI, with startups targeting varied applications. Chemix, a California-based startup, has developed MIX™, a GenAI platform leveraging a vast dataset of proprietary experimental data from prototype cells. Their AI models predict battery materials' performance and forecast cycle life, providing three ready-made chemistries: Opal, Jade, and Sapphire. Eonix's ATLAS platform automates materials discovery for batteries, accelerating development timelines while reducing costs. SES AI focuses on advanced Li-Metal batteries for land and aerial applications, utilizing their in-house Hermes discovery platform and Avatar, an AI-powered digital twin, to enhance battery performance. Aionics, based in Palo Alto, is building AI capabilities to test 10,000 candidates/second from a database of billions of molecules. They also use Generative models and physics-based simulations trained on existing battery materials data to design new molecules with targeted applications.

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Pack Design

Voltx.ai's custom battery-pack generator platform uses a patent-pending algorithm to create thousands of potential designs. Oorja Energy is an Indian startup simplifying complex engineering design by combining physics-based modelling and ML to improve battery accuracy and efficiency. They provide custom battery pack design tools for various cell form factors as well. Tel Aviv-based Addionics, with over $30 million in funding, has developed a proprietary platform to optimize battery cell structures for specific performance outcomes.

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Lifecycle Management

In the battery lifecycle management space, our portfolio company Sheru's ScaleBat platform aims to be a Battery Copilot, offering comprehensive tracking and optimization of battery life, integrating with ERP systems and IoT devices. Coulomb AI provides real-time analytics on battery performance, and facilitates seamless transition to second-life applications, thereby reducing the TCO. Adiabatic, BatteryOK and Altergo are other Indian startups innovating sophisticated BMS platforms. 

Globally, large players like Peaxy, TwAIce and Element Energy have built advanced battery analytics platforms and count large corporations like Honeywell, Schlumberger, Audi, Mercedes, BMW etc. as customers.

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Pricing-in the value

A relatively newer push in the innovation of battery chemistries is through the advent of Generative AI, which addresses three major problems in battery design:

1. Infinite Permutations and Combinations: With countless potential battery materials, it's challenging to prioritize which to test.
2. Long Testing Times: Iterating on designs is slow, delaying improvements.
3. Black Box Nature of Batteries: The complex internal interactions make it difficult to predict how design changes will impact performance from a high-level perspective.

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Opportunities for building in, and for India

India is experiencing rising R&D and funding in the battery ecosystem, with market revenues projected to reach $27.70 billion by 2028. Various chemistries show promise compared to conventional Li-ion batteries. Higher energy density chemistries include Si-C composite anodes, nanophosphate cathodes, silicon anodes, lithium-sulfur, and solid-state batteries. Lower-cost chemistries, like sodium-ion and aluminium-air, and higher life cycle chemistries, such as redox flow batteries, are also emerging. Sodium-ion and redox flow batteries offer higher safety.

Lower-cost alternatives with abundant raw materials, like Na-ion and Li-S, are likely to attract significant interest in the price-sensitive Indian market alongside the growth of conventional Li-ion LFP chemistries.

In India specifically, there is a vacancy for startups developing GenAI-led battery discovery platforms with proprietary datasets tailored to Indian form factors, especially E-2 and 3W, emphasizing customization to meet the country's diverse mobility needs with the presence of multiple relevant low-cost chemistries. 

The raw material supply chain and subsequent manufacturing are also whitespaces in the Indian battery ecosystem, with clunky and inefficient workflows that could be enhanced with AI-led tools built with this vertical focus.

If you're pioneering in this field, we'd love to collaborate!
Reach out to us and let's shape the future of energy together.