EV Fleet Charging Load Balance Planner

Plan an EV depot around energy, power, and demand charges

Charging a fleet is not just a question of how many kilowatt-hours the vehicles need by morning. Depot operators usually have to satisfy three limits at the same time: enough daily energy to refill the fleet, a low enough peak kW to avoid painful demand charges, and a realistic number of chargers that can be active together without overloading the site. This planner brings those constraints into one place. Instead of forcing you to build a custom spreadsheet each time a route changes, you can enter the core operating assumptions and quickly see whether the planned charging window is comfortable, tight, or impossible under the current setup.

The calculator is especially useful when the answer is not obvious from gut feel. A depot can have plenty of total energy over an eight-hour window and still run into trouble because too many vehicles need to charge at once. The reverse also happens: a site may have very high peak capacity but still not deliver enough daily energy if the charging window is short or charger efficiency is poor. By showing per-vehicle grid energy, total daily energy, average site load, peak load, minimum charger count, and monthly cost estimates together, the tool helps you judge the whole system rather than a single headline number.

What each input means in fleet operations

Number of Fleet Vehicles is the count of vehicles that must be supported during a normal charging day. In this model, the fleet is treated as if each vehicle behaves similarly, so this number should reflect the group you want to plan for, not necessarily every vehicle you own. If only the overnight shift uses this depot, enter that overnight group. Average Daily Miles per Vehicle converts route activity into energy demand. It is an operational average, so it should describe a typical day or a conservative busy-day assumption rather than the best-case day with the shortest routes.

Vehicle Efficiency tells the planner how much battery energy is used per mile. A value of 0.35 kWh per mile means a vehicle typically consumes 35 kWh over 100 miles. Battery Capacity per Vehicle caps the amount of energy that can practically be stored in one vehicle during the modeled cycle. The planner also asks for Average Arrival State of Charge and Required Departure State of Charge. Those two values matter because a depot often has a service rule such as arrive around 30% and leave at 90%. Even if route energy alone seems small, a high morning target can still force significant overnight charging.

The site-side inputs describe how fast the depot can deliver that energy. Charger Power is the rated power of one active charger in kW. Charging Window per Day is the number of hours available for fleet charging during the planning period. Maximum Simultaneous Chargers is the concurrency limit: how many chargers can realistically run at once because of hardware, transformer, utility, or operational limits. Charging System Efficiency adjusts battery energy into grid energy, recognizing that cables, power electronics, and thermal losses mean the utility meter will always see more energy than the battery actually stores. Finally, Energy Cost per kWh estimates monthly usage cost while Demand Charge per kW estimates the monthly fee tied to the site peak.

How the planner converts those inputs into results

The first step is to estimate how much useful battery energy one vehicle needs in a day. The route-based portion is daily miles multiplied by vehicle efficiency. The state-of-charge portion is battery capacity multiplied by the gap between target and arrival state of charge. The model then uses whichever of those two needs is larger, because a practical plan has to satisfy both route usage and departure readiness. That energy need is capped at battery capacity so the tool does not imply a single vehicle can absorb more than a full battery in one cycle. After that, charging efficiency converts battery energy into the grid energy that the site must actually buy.

Total daily energy is simply that grid energy per vehicle multiplied by the number of vehicles. Average load spreads the total energy evenly across the charging window, while peak load assumes the highest allowed number of chargers operate at full power at the same moment. The minimum charger count rounds upward because you cannot install or dispatch a fraction of a charger. In other words, if the math says 3.2 chargers are needed, the planner reports 4 because a real depot must cover the full requirement.

If you like to think of the planner in more abstract terms, the page also keeps the generic mathematical view below. It is the same idea expressed more generally: a result is a function of several inputs, and some results are weighted sums. In the fleet context, those weights become things such as efficiency losses, charger rating, and concurrency limits.

Worked example using the default values

Suppose your depot supports 60 vehicles, each averaging 85 miles per day at 0.35 kWh per mile, with 120 kWh batteries. Vehicles arrive around 30% state of charge and must leave at 90%. Each charger is rated at 150 kW, the charging window is 8 hours, the site allows 20 simultaneous chargers, charging efficiency is 92%, energy costs are $0.11 per kWh, and demand charges are $15 per kW of peak demand. The route-energy estimate is 85 × 0.35 = 29.75 kWh per vehicle. The state-of-charge refill estimate is 120 × 60% = 72 kWh per vehicle. Because the planner uses the larger need, it models 72 kWh of battery energy per vehicle.

After adjusting for 92% charging efficiency, per-vehicle grid energy is about 78.3 kWh. Across 60 vehicles that becomes roughly 4,695.7 kWh per day. Spread across an 8-hour window, the average load is about 587.0 kW. Peak load, however, depends on concurrency rather than average energy, so 20 chargers at 150 kW create a possible 3,000 kW site peak. Minimum full-power chargers required is the total daily energy divided by 150 kW × 8 hours, rounded up to 4 chargers. The energy portion of monthly cost is about $15,495.65, while the demand-charge estimate is $45,000 per month. That contrast is exactly why depots care so much about staggering sessions: peak kW can dominate the bill even when daily energy is manageable.

How to interpret the result panel

When you press Plan Charging Load, the result panel summarizes the planner in plain language. Per-vehicle grid energy tells you how much electricity the utility meter must deliver for one vehicle under the current assumptions. Total daily energy scales that across the fleet. Average load is useful when checking overall service sizing and whether the charging window has enough room in principle. Peak load at max concurrency is the number to compare with transformer limits, service entrance limits, and monthly demand charges. Monthly energy cost and estimated monthly demand charge separate the two major utility bill drivers so you can see whether the problem is mainly energy volume or short periods of high simultaneous charging.

The feasibility sentence at the end is the planning shortcut. If the minimum chargers needed exceeds your allowed simultaneous charger count, the modeled schedule does not fit inside the current window at rated power. That usually means one of five actions is required: extend the charging window, reduce daily miles, improve efficiency, lower the departure state-of-charge target, or add more available charger capacity. If the schedule is feasible, the result does not guarantee perfect real-world operation, but it does mean the basic energy arithmetic works under the model assumptions.

Scenario comparison table

A planner is most useful when you compare scenarios instead of trusting one run. The table below keeps the same default vehicle and charger assumptions but changes only the number of vehicles. That isolates how fleet growth affects total daily energy, average load, and minimum required charger count. Notice that peak load stays at 3,000 kW in all three examples because the concurrency limit is unchanged at 20 chargers. In practice, this means fleet growth may first show up as tighter daily scheduling before it changes your maximum theoretical site peak.

That pattern gives you a practical planning clue. If fleet size rises from 60 to 72 vehicles and the departure target remains the same, the energy bill rises roughly in proportion to the added energy, but the required charger count also steps up from 4 to 5. That one-step jump is operationally important because it means the schedule has less slack. Small changes in fleet size, route length, or charging window can therefore trigger a sudden need for more active charging positions even before the utility side changes.

Assumptions, edge cases, and sanity checks

This calculator is intentionally a fast planning model, not a minute-by-minute charging optimizer. It assumes the vehicles are similar enough to summarize with one average miles value, one efficiency value, one battery size, and one pair of arrival and departure state-of-charge targets. It also assumes active chargers can deliver their rated power for planning purposes, even though real charging often tapers as batteries fill. Demand charges are estimated from the peak-load calculation, not from a utility tariff with seasonal ratchets or time-of-use rules. Because of that, the output is best used for early sizing, scenario comparison, and operational conversation rather than final engineering sign-off.

There are also a few input combinations that deserve special attention. If arrival state of charge is already above the target, the state-of-charge gap contributes zero energy, but route energy can still require charging. If daily miles times efficiency implies more energy than the battery can hold, the model caps the per-vehicle battery need at battery capacity. That is not a hidden fix; it is a warning sign that the route, battery, or charging opportunity assumptions may be inconsistent. Likewise, if the result shows a very low minimum charger count but a very high peak load, that usually means the site could meet daily energy with relatively few chargers if sessions are scheduled carefully rather than turned on all at once.

A good sanity check is to change one input at a time and confirm the direction of the result. Increase miles and total daily energy should rise. Shorten the charging window and average load should rise. Increase concurrency and peak load should rise, but minimum chargers needed should not change unless you also change other assumptions. If a result moves in an unexpected direction, it is usually a clue that the operational meaning of one input needs another look. That kind of quick sensitivity testing is often more valuable than the baseline number itself.

Using the output to make better fleet decisions

The most practical use of this planner is to compare operating strategies before spending money. You can test whether extending the window by one hour is cheaper than adding more simultaneous fast charging, whether a lower departure target meaningfully reduces demand charges, or whether a modest improvement in vehicle efficiency delays a service upgrade. In many depots, the winning strategy is not the highest charger power but better staggering: match enough chargers to daily energy needs, then use scheduling or software to keep peak concurrency below the costly part of the utility tariff. The calculator does not replace a detailed charging management platform, but it gives you a reliable first pass at the core question: can this fleet get the energy it needs without creating an avoidable peak problem?