Product client
EV Fleets, Charging Operators, Grid OperatorsMaturity
CommercialisedFind out more about this product's availability
Product end user
EV Fleets, Charging Operators, Grid OperatorsKeep track of your energy costs & emissions, and benefit from custom autonomous smart charging.
We developed a platform featuring high performing forecasting algorithms and a powerful optimisation engine to intelligently predict and optimise flexibility in EV charging.
Our industrial protocols allow communication with EV chargers, stationary batteries and energy management systems. Our cloud also enables the ingestion of real time data coming from electrical grids, electric meters, onsite solar to inform our optimization models. Finally, to guarantee the authenticity and integrity of the data, our internal processes are registered in a ledger.
Our forecasting algorithm is a key element in our solution as this greatly minimises dependency on end user engagement and sets the environment for high frequency adjustments to enable grid services. Our machine learning algorithm predicts the departing time of EVs which allows us to evaluate the flexibility of each session and better optimise their charging schedule.
Our optimisation engine is customisable based on the customers’ needs. We can provide grid reliability solutions, as well as valuable services for fleet operators such as a “renewable energy first” option, power costs and peak power demand savings, and early battery degradation prevention.
So far, our smart charging algorithms have been able to unlock up to:
- 80% reduction in peak loads.
- 50% reduction in charging costs.
- 70% reduction in charging CO2 emissions.
- 40% reduction in EV battery degradation.
The Bia platform can easily connect to all types of charging infrastructure, no matter the brand and model, as long as it has connectivity. As the optimisation engine is highly parameterisable, we can optimise for a single or several weighted features depending on what is relevant for our customers.
The platform is highly modular and can operate autonomously in different applications by either forecasting drivers’ charging needs, by collecting users’ inputs once a session starts, or by considering a fleet schedule.
We are keeping track of the technology and methods we develop via a trade secret filing system at the World IP Organisation
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