From Superchargers to eMobility AI: former Tesla engineer positions Quantum Drive as the “Google Maps for EVs”

The idea behind Quantum Drive was sparked by a personal experience at the wheel.

“I didn’t plan to stop for a charge, but I ended up needing to. It was an inconsistent experience — and I didn’t like it,” recalls Daniel Fernández, co-founder of the startup, in conversation with Mobility Portal Europe.

That journey in a Tesla became the catalyst for a project that now operates as a web app across Europe.

The platform allows users to plan routes based on real variables affecting electric vehicle (EV) consumption: kilometre-by-kilometre topography, temperature, wind, average speed, passenger load, use of A/C, among others.

“It truly simulates a real-world trip and can tell me what my actual range will be under those conditions,” he explains.

The system merges this data with a database of over 500 EV models, offering suggestions on where to stop, when, and for how long.

What sets it apart is its use of AI models trained with real vehicle data, using machine learning to fine-tune energy consumption predictions for each stretch of road.

Currently, the margin of error stands at 5% — “as long as speed is maintained,” Fernández notes. “If you go a little over the limit, energy use increases significantly.”

From technical expertise to entrepreneurship: the Quantum Drive story

Fernández worked at Tesla during the pandemic, based in London.

“I experienced the deployment of charging infrastructure across the United Kingdom (UK) and Ireland — it really helped me understand the EV sector,” he says.

After Tesla, he joined Wallbox as a project manager and participated in the development of the Supernova DC charger.

“At Wallbox we were focused on hardware — dealing with moulds, connections, integrating software. Very different from what I do now: we build software.”

He later worked at One Solar, specialising in grid-connected storage systems, where he deepened his knowledge of battery degradation — an insight now embedded in Quantum Drive.

The platform can estimate battery health based on driving behaviour.

“If I’m always fast-charging, driving up mountains, flooring it… how has that affected my battery?”

This feature is available in two ways: by connecting directly to the vehicle, or through user-supplied data and estimated behaviour.

“We’re using academic research papers to estimate battery state of health — and that’s vital for users, because warranty coverage is at stake,” Fernández points out.

Looking ahead: OEM integrations and real-time navigation

Quantum Drive’s ambition is to scale. The first product is the predictive route planner. The second, now in development, is a real-time connected navigation system that links directly with public charging networks.

The third, an AI-powered assistant that can respond to questions, anticipate diversions, and adapt to live driving conditions.

“We’re developing each product independently, taking care with every detail — and then we’ll bring them together,” Fernández explains.

Since March 2025, the startup has been part of Lanzadera’s high-performance programme.

“It helps us define clear goals and a solid product strategy. It’s like having a product, marketing, and admin department in a single incubator,” he says.

Quantum Drive is currently in talks with carsharing companies, specialised media, and mobility platforms, and is seeking to integrate its software into in-vehicle infotainment systems.

“Google is already integrating EV data into some cars. I’d like Quantum Drive to be in that position — I believe we can do it better,” he says confidently.

The team is particularly targeting Asian manufacturers, as their web app is already available openly to any user in Europe looking to plan an EV trip without surprises.

“The goal is to give drivers all the information they need: when to stop, how much to charge, how their driving impacts the battery — and how to travel with confidence,” Fernández concludes.

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