Electric vehicle route planning: Requirements for your software

Route planning for electric vehicles connects jobs, time windows and vehicle capacity with the available energy and charging plan. Suitable software must therefore make it clear whether a route can be completed within these conditions. Reliable input data, visible assumptions and a defined way to handle deviations are crucial when assessing your requirements.
The shortest route does not answer every operational question. A vehicle must reach its work location on time, complete the job and then be able to reach its next planned stop. Charging stops and their place in the schedule therefore belong in the planning process from the start.
What information does the route plan need?
Start with the jobs: locations, desired arrival windows, time on site, required equipment and transport needs. Add the available vehicles, their operating hours and relevant operational restrictions. A vehicle unsuited to the job does not become suitable simply because its calculated range is sufficient.
For energy planning, you need a current or transparently assumed starting state, the planned energy demand and an operational reserve. If vehicle data is to arrive automatically, access, freshness and completeness must be checked for the vehicles actually in use.
Research on electric fleet planning explicitly treats range limits and the scheduling of charging stops as connected constraints. For your requirements catalogue, this means asking for route and charging plans to be explained as one continuous process. Source: research on route and charging planning for electric fleets.
Plan charging stops with realistic time windows
A possible charging location becomes a useful planning point only when it fits the route. Account for the journey to it, access, the stop itself and onward travel. Also check whether the vehicle can take on the required energy under the expected conditions.
Do not assume the rated power of a charging point is the power the vehicle can achieve continuously. Planning requires a justified assumption about the usable charge within the available time window. If this is unclear, the plan should show the uncertainty and include an operational alternative.
Charging time at the site must fit arrival, the next departure and available spaces. If several vehicles need the same time window, a separate calculation for each vehicle is insufficient. Check their combined use of charging spaces and the operational priority of upcoming assignments.
Make planning rules and reserves visible
Define which conditions are mandatory and where flexibility exists. A confirmed time window, required vehicle equipment and a minimum reserve can form fixed limits. The order of individual flexible jobs, by contrast, may be adjusted.
Every reserve needs a clear purpose. It might account for uncertainty in energy demand or the distance needed to reach an available fallback option. An arbitrary percentage without a connection to the assignment is not a reliable justification.
During a software test, ask what happens when information is missing. Is a route blocked, flagged with a warning or approved under documented assumptions? Your team should recognise which decision relies on measurements and which on provisional planning. Find out more in range planning for electric fleets.
Practical example: An additional appointment is added to a route
Fictional planning example: A service vehicle is scheduled to visit three work locations and return at 3:00 pm. Planned energy demand is 34 kWh. For this example, available energy is assumed to be 46 kWh, of which 8 kWh remains as the agreed reserve. This leaves 38 kWh available for the planned journeys.
An additional job increases estimated demand to 41 kWh. Under these assumptions, the expanded plan is not approved. Dispatch checks whether to reassign the appointment or include a suitable charging stop, taking access and time requirements into account.
The decision is documented with the new plan version. Entering the additional distance into the navigation system alone is not enough. This case shows why the assessment must be repeated when a route changes. All figures are purely illustrative.
Practical tool: An acceptance test for your route planning
Prepare five typical cases and record the inputs, expected warnings and person responsible for approval in each one:
A regular daily route with complete starting data.
A route with a fixed appointment and a tight charging window.
An additional job added at short notice during the day.
A vehicle with an outdated or missing state-of-charge value.
An unplanned outage at the intended charging location.
The software should make its decision understandable in every case. Also check how changes reach dispatch and the affected drivers. A sound plan only helps when the current version is used in the field.
After a pilot phase, analyse deviations by cause: incomplete job information, unsuitable energy assumptions, additional journeys or organisational delays. Improve the affected input data specifically. A documented process for electric fleet notifications supports the handling of urgent deviations.
Turn your typical routes and required charging information into concrete requirements: review your electric fleet needs with StromNow.
Frequently asked questions
Does every route planning process need current vehicle data?
Current data can support planning, but it is not automatically available in every workflow. Define a reliable starting value and a fallback process. Label assumed values so that the person approving the plan understands its limits.
May the software approve a route when the charge level is missing?
Your operational rules should define this. Check whether confirmed manual information is sufficient or an additional check is needed. Missing data should not silently be interpreted as sufficient energy.
How can I tell whether planning works in daily operations?
During the pilot, check appointment completion, unplanned charging stops and the effort required for plan changes. Document the causes of deviations. This reveals which assumptions or processes need improvement.