February 14, 2025
Let’s talk briefly about charge management systems (CMS) first and then get into managed services. A CMS is used by fleet operators for visibility into energy consumption of the electric fleet and to effectively optimize cost of electricity. If a fleet has more than a few EVs, the cost of electricity may ratchet up quickly due to what we all know as “demand changes”. It’s like surge pricing. If you want the service now when everyone else wants the service it’ll cost you a whole lot more.
The expectation of lower overall fleet operating costs by integrating EVs hinges on the capability to minimize cost of electricity as fuel, which can be as little as one quarter the cost per mile or fossil fuel. CMS smooths the electricity load, avoids demand charge ratchets, and delivers lower cost electricity as fuel. It can also constrain peak electricity load and ensure that a maximum power is never exceeded, avoiding electricity distribution upgrades thereby lowering the capital expenditure of the charging system build. CMS is necessary and beneficial.
However, EV energy consumption fluctuates throughout the year due to environmental conditions. January trips require more energy than July trips, and kilowatt-hours per mile increase with adverse road conditions such as rain and snow, often doubling energy usage. Despite these fluctuations, operational demands of the fleet remain unchanged, necessitating adjustments to charging setpoints and shifting strategies in the worst cases from overnight charging to midday top-ups. Can your CMS keep up?
The Limitations of CMS in Operational Intelligence
Relying solely on CMS to deliver energy cost efficiency overlooks the most critical aspect —fleet operational intelligence. The primary mission of a fleet is operational readiness, which cannot be compromised or altered simply to achieve fuel cost savings.
The key challenge for fleet operators and CMS setup is determining the right settings for charge management. There is the expected case, the worst case, and everything in between.
Consider a few real-world questions:
- What happens when a vehicle returns late or with a lower state of charge (SOC) than expected; Will it be ready the next day based on the preprogrammed settings?
- What if a vehicle needs to depart earlier than expected; When will it need a top-up or recharge?
- How does varying weather affect energy consumption and how does that impact the charging strategy?
- When is mid-day charging a reasonable strategy for operations and energy cost savings?
- Where should opportunity charging be placed? How often would if be needed?
Because CMS collects all this data it can be analyzed for key insights and incorporated into the charging strategy. The proactive approach is of course simulating these operational scenarios to determine the most effective smart charging settings. More important in simulation is getting the charging system design right with out underbuilding, leading to ineffective operations, or overbuilding, bloating the capital budget and bumping payback way out in time. Did your engineering firm account for these variations before design?
So what About Pattern Recognition?
Even if machine learning (ML) and artificial intelligence (AI) were deployed to identify relevant patterns and offer actionable insights, such approaches require vast historical charging data—data that currently does not exist. Furthermore, historical data continuously evolves with every new EV deployment, shifting electricity tariffs, changing grid demand patterns, and evolving renewable energy generation. AI is simply not a viable solution in the near term, but will be in the long term.
The Answer to Avoiding Reactive, Ineffective Settings, is Managed Services
Operational reliability comes with active management and constant observation, a role that many fleet operators do not have for their EVs. Knowledge about what’s working as expected, where is underperformance and why, and system faults that go undetected or are uninterpretable.
Achieving optimal results requires an in-depth understanding of each fleet’s unique operations, vehicles, and charging infrastructure. Engineers expert in fleet operations analysis and optimal charging strategy development can help with:
- Assessing current operations and constraints.
- Developing an effective, data-driven strategy.
- Creating a tailored charging schedule.
- Validating system performance under various conditions.
- Deriving CMS settings for smart charging.
Contact us today to optimize your fleet’s charging strategy, meet operational requirements, and minimize costs. We have vast experience, supporting electric fleets of hundreds of vehicles in a given location. We’re dedicated and lower cost than relying on your engineering firm. They design, we optimize.