In an interview with Aditya Rangroo, Ursaa Energyworx Founder Kapil Sharma saidIf batteries degrade faster than expected, the entire EV economics model falls apart
The EV ecosystem is evolving rapidly—what are some of the biggest challenges fleet operators face today when it comes to battery performance and efficiency?
Everyone talks about EV adoption as if it is a solved problem. It is not. Fleet operators are not struggling to buy EVs; they are struggling to run them efficiently.
The biggest issue is unpredictability. Two identical vehicles, on the same route, on the same day, can deliver completely different performance, and most operators have no idea why. Battery behaviour is not linear. It is affected by temperature, driving style, and charging habits. Yet, most fleets still operate without real visibility into these factors. So what happens? You don’t optimise, you react. And that is where the real cost creeps in.
UrsaaEnergyworx focuses on battery intelligence and telematics—how do data and predictive analytics change the way EV fleets are managed?
Right now, most EV fleets are managed based on symptoms, not causes. You see reduced range or a breakdown, but you don’t know what led to it.
Data changes that. Predictive analytics takes it even further. At Ursaa, we are not interested in just showing dashboards, which is useless if it doesn’t drive decisions.
We focus on the questions that actually matter:
- Which batteries are going to fail before they fail?
- Which usage patterns are quietly degrading battery lives?
- What operational changes can immediately improve performance?
Battery health is critical to EV adoption. How can technology help extend battery life and reduce total cost of ownership for fleet operators?
If batteries degrade faster than expected, the entire EV economics model falls apart. What we have observed is that most damage isn’t sudden, it is gradual and preventable.
Technology helps in three key ways:
- It flags early signs of degradation before they become costly problems
- It corrects poor charging behaviour, one of the biggest silent killers
- It aligns vehicle usage with battery capabilities instead of overloading the asset
You don’t need magic, you need visibility and discipline. Technology enforces both.
We often hear about range anxiety—do you think data-driven insights can help address this concern for both businesses and consumers?
Range anxiety exists because the system is misleading, not intentionally, but because it relies on static estimates in a dynamic environment.
If your range estimate doesn’t account for traffic, load, terrain, or temperature, it’s unreliable.
Data fixes that. When range becomes predictive and context-aware, it stops being a guess and starts being a commitment. For fleets, that means fewer disruptions. For consumers, it builds trust.
And once trust is established, range anxiety fades quickly.
How is AI and IoT shaping the future of electric mobility, especially in emerging markets like India?
In markets like India, complexity is the default. There is extreme weather, unpredictable traffic, inconsistent infrastructure, and highly variable usage patterns.
If you try to manage this with static systems, you will fail. IoT provides the raw signalcontinuous data from vehicles and batteries. AI transforms that data into real-time decisions.
This combination is what makes EV operations viable at scale in such environments. Without it, you are essentially guessing, and guessing doesnot scale.
What role do you see battery intelligence platforms playing in accelerating large-scale EV adoption across sectors like logistics and last-mile delivery?
Let’s be honest: no logistics company adopts EVs just because it sounds good. They will switch when it makes operational and financial sense.
Battery intelligence platforms make that shift viable. They:
- Reduce uncertainty
- Improve uptime
- Protect the most expensive asset in the system, that is, the battery
In high-utilisation sectors like last-mile delivery, small inefficiencies quickly turn into significant losses.
As India pushes towards electrification, what are the key gaps in infrastructure or technology that still need to be addressed?
Everyone points to charging infrastructure, and yes, it matters. But the bigger gap is intelligence.
We still lack:
- Standardised battery data across OEMs
- Deep, scalable visibility into battery health
- Seamless integration between vehicles, chargers, and fleet systems
Right now, the ecosystem is fragmented. Until these systems start communicating with each other, scaling EVs efficiently will remain more difficult than it should be.
Looking ahead, how do you see the intersection of energy, data, and mobility evolving over the next 3–5 years?
These three domains are set to converge, and faster than we can imagine now.
Vehicles won’t just consume energy; they will become part of the energy ecosystem.
We will see:
- Batteries managed as high-value assets, not just components
- Charging decisions driven by data, cost, and grid conditions
- Platforms at the centre, orchestrating everything in real time
The winners won’t be those with the most vehicles. They will be those who understand and control the data layer. That’s where the real leverage lies, and that’s exactly where we are building.
