At the core of the report is the Battery Control Algorithm, a linear optimisation framework that manages charging, V2X dispatch and reserve battery sizing. The approach treats the depot’s swappable battery pool as a dynamic stationary storage asset and optimises its operation against day-ahead electricity prices, photovoltaic generation, fleet swap schedules and state-of-charge constraints.

The analysis includes a full-year simulation of the BUZZZ Malta ride-hailing fleet and shows total annual savings of €9,716. Of this, €7,157 comes from peak shaving and time-of-use arbitrage, €254 from PV self-consumption, €832 from behind-the-meter V2B, and €1,473 from V2G grid export. Overall, 76% of the savings are generated by unidirectional smart charging, while 24% comes from bidirectional V2X.

The report highlights how high-resolution vehicle energy modelling improves accuracy compared to earlier assumptions, and shows that reserve battery packs required for operations can become cost-neutral through energy revenues under certain conditions. It also introduces a scalable methodology to evaluate smart charging and V2X potential in swappable battery fleets, where continuous battery exchanges and operational constraints require more advanced optimisation than in conventional EV fleets.

The results represent an upper-bound estimate based on an aggregated battery model, meaning real-world savings may be lower depending on operational conditions, infrastructure and regulatory frameworks. Overall, D3.3 provides a quantitative basis for prioritising smart charging strategies and assessing the business case for V2X-enabled solutions in modular swappable battery systems.

The full deliverable is available here