A practical guide to service radius, daily charging capacity, parking-space coverage and fleet sizing
A 200-space parking facility does not need 200 fixed chargers. In many locations, the more useful question is whether one charging asset can move between parked vehicles and complete the right number of requests before drivers leave. Door Energy develops mobile energy-storage and charging systems for commercial, emergency and industrial use, including an autonomous charging robot designed to travel to vehicles inside structured parking environments.
For most early-stage projects, one autonomous Mobile EV Charger can be evaluated against approximately 80-250 parking spaces within an 80-150 m straight-line service radius. This is a planning range, not a fixed product promise. The correct result depends on EV share, request rate, energy per session, vehicle dwell time, route complexity and the available recharging window.
This guide converts those variables into a repeatable sizing method. It uses international charging-session data as reference points, combines them with the published specifications of the Door Energy MCP-D, and shows how office, retail, residential and fleet sites can produce very different equipment requirements even when their parking-space counts look similar.
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When a project team says that one unit “covers 200 spaces,” the phrase should mean that the machine can physically reach those spaces and serve the requests generated within that zone. It does not mean that 200 vehicles can charge at the same time. A mobile system separates the location of the charger from a permanently dedicated charging bay, but it still works within limits set by energy capacity and task time.
This distinction is especially important for buyers comparing fixed infrastructure with a charging robot. A fixed charge point is normally tied to one adjacent bay. By contrast, a Mobile EV Charger can share charging capacity across many ordinary parking spaces. However, mobility only creates value when the robot can reach vehicles quickly, deliver enough energy and return for replenishment without missing departure deadlines.
| Site type | Initial spaces per unit | Suggested radius | Typical daily tasks |
| Office campus | 120-250 | 100-150 m | 4-8 |
| Retail / public parking | 60-150 | 60-120 m | 6-10 |
| Hotel / residential parking | 150-300 | 100-200 m | 3-7 |
| Airport parking zone | 60-120 | 60-120 m | 6-10 |
| Logistics / fleet depot | 30-80 | 50-100 m | 6-12 |
| Industrial site | 50-120 | 50-120 m | 5-10 |
These ranges are intentionally broad. An office vehicle may remain parked for eight hours, allowing the scheduler to sequence several requests calmly. A retail visitor may leave after 60-90 minutes, so the same number of requests creates a much tighter response requirement. Meanwhile, a logistics van may need two or three times the energy of a short passenger-car top-up.
Global electric-car sales exceeded 20 million in 2025 and represented roughly one quarter of new-car sales worldwide, according to the International Energy Agency. A parking project designed around today’s EV share can therefore become undersized before the equipment reaches the end of its service life. For a credible investment case, model at least three demand conditions: current, expected three-year and high-growth.
| Planning case | EV share | Daily request rate | Purpose |
| Current conservative | 10% | 15-20% | Minimum operating case |
| Three-year standard | 20% | 20-30% | Primary equipment sizing |
| High-growth | 30-40% | 30-40% | Expansion trigger |
| Dedicated electric fleet | 50-100% | 20-60% | Shift-based planning |
A useful design target is to keep routine demand below 70-85% of stable daily capacity. The unused margin is not wasted capacity. It absorbs urgent departures, temporary route blockages, connection retries, seasonal peaks and scheduled maintenance.
The first calculation estimates how many charging requests the parking population will generate each day. Five inputs are sufficient for an early Mobile EV Charger model: total spaces, occupancy, EV share, the percentage of EV drivers requesting service, and a peak or special-demand factor.
Daily charging requests: Q = P x O x E x R x K
| Symbol | Meaning | Example input |
| P | Total parking spaces | 200 |
| O | Average occupancy | 85% |
| E | EV share among parked vehicles | 20% |
| R | Share of EVs requesting service that day | 25% |
| K | Peak / seasonal adjustment factor | 1.0-1.3 |
| Q | Expected daily charging requests | Calculated result |
For a 200-space office site with 85% occupancy, 20% EV share and a 25% daily request rate, the result is 8.5 requests per day before any peak adjustment. The site is therefore not a “200-vehicle charging project.” It is an approximately nine-task-per-day project.
A large difference exists between a driver who needs enough energy to reach home and a commercial van preparing for another route. U.S. public fast-charging data covering about 2.4 million paid sessions found an average duration of 42 minutes and an average delivery of 22 kWh. That figure is useful as an international passenger-car reference, although every project should replace it with local data after a pilot.
| Vehicle / task | Planning energy per request | Operating objective |
| Passenger-car short top-up | 15-25 kWh | Add practical return range |
| Retail parking visitor | 20-30 kWh | Support the onward journey |
| High-utilization passenger vehicle | 30-45 kWh | Prepare for the next work period |
| Electric light commercial van | 30-60 kWh | Support a delivery route |
| Emergency roadside top-up | 10-30 kWh | Reach a safe or fixed charging location |
| Industrial electrical load | Load-specific | Power equipment or temporary operations |
Average charging power should also be separated from rated power. A vehicle may not accept the charger’s maximum output throughout the session. State of charge, battery temperature, vehicle limits and tapering near high SOC all affect the real average. Consequently, a 100 kW rating must not be converted directly into a promise that every 50 kWh session will finish in 30 minutes.
Dwell time determines whether requests can be queued or must be served immediately. Long-stay office and residential users may tolerate scheduled service later in the day. Retail users need faster confirmation. Fleet vehicles may have the clearest deadlines of all because each task is linked to a dispatch schedule.
| Parking context | Illustrative dwell time | Scheduling implication |
| Quick retail visit | 0.5-2 hours | Short queue; rapid response |
| Office parking | 6-9 hours | Sequence tasks around departure time |
| Hotel / residential | 8-12+ hours | Shift work to off-peak periods |
| Airport long stay | 1-5 days | Prioritize by return time, not arrival time |
| Fleet depot | 1-10 hours | Prioritize by next dispatch |
The Door Energy MCP-D autonomous charging robot combines onboard energy storage, DC charging, autonomous movement and intelligent scheduling. Its published configuration includes 105 kWh battery capacity and up to 100 kW charging power. A separate 50 kW bidirectional charging-and-discharging function is described as configuration-dependent; therefore, final input and bidirectional output values should be confirmed for each project rather than treated as universal.
| Published parameter | MCP-D reference | Planning significance |
| Battery capacity | 105 kWh | Limits energy available between replenishment cycles |
| Maximum charging power | Up to 100 kW | Sets the output ceiling, not the session average |
| Connector | CCS1 / CCS2 | Supports American- and European-standard projects |
| DC voltage range | 200-1000 V | Supports different vehicle voltage platforms |
| Communication | OCPP 1.6J | Enables monitoring and scheduling integration |
| Autonomous level | L4 | Supports autonomous parking-facility movement |
| Maximum travel speed | 10 km/h | Maximum value; not the indoor planning speed |
| Operating temperature | -20 to 65 C | Supports a broad operating range |
| Protection rating | IP55 | Relevant to site environmental assessment |
| Cycle life | >5,000 cycles | Stated at 90% DOD and 80% EOL |
| Thermal management | Liquid cooling | Supports controlled battery operation |
| Gradeability | >20% | Relevant to garage-ramp assessment |
Rated battery capacity should not be treated as fully deliverable energy. A Mobile EV Charger must reserve energy for mobility and battery protection while allowing for conversion losses, temperature effects and operating policy. At feasibility stage, a combined planning factor of 80-90% is reasonable until project-specific test data is available.
Deliverable energy per cycle: 105 kWh x usable-energy factor
Using an 85% factor gives 89.25 kWh of planning energy per cycle. This is not a new product rating. It is a conservative engineering allowance used to prevent the fleet model from assuming that every nominal kilowatt-hour is available to customer vehicles.
| Average energy per task | Mathematical tasks per cycle | Recommended planned tasks |
| 15 kWh | 5.95 | 5 |
| 20 kWh | 4.46 | 4 |
| 22 kWh | 4.06 | 3-4 |
| 25 kWh | 3.57 | 3 |
| 30 kWh | 2.98 | 2-3 |
| 40 kWh | 2.23 | 2 |
| 50 kWh | 1.79 | 1-2 |
Every task includes much more than energy transfer. The robot must accept a request, plan a route, travel, identify the vehicle, align, connect, validate communication, charge, disconnect and either continue to the next job or return. Manual plug-in adds staff response time, while automated connection requires compatible vehicle positioning and site design.
| Task element | Illustrative time |
| Request validation and route planning | 1-2 min |
| Travel to the target vehicle | 3-7 min |
| Positioning and safety confirmation | 2-4 min |
| Automatic connection or manual plug-in | 2-5 min |
| Delivering 22 kWh at 50 kW average | About 26 min |
| Disconnection and task confirmation | 2-4 min |
| Return travel or next-task movement | 3-7 min |
| Exception allowance | 3-5 min |
| Illustrative total task cycle | 42-60 min |
Stable daily capacity: Minimum of energy-limited tasks and time-limited tasks
Suppose the unit completes two effective energy cycles per day. At 89.25 kWh per cycle and 22 kWh per request, energy capacity supports about eight tasks. Even if the time schedule appears to fit 10 or 12 tasks, the project should initially plan around eight because energy becomes the controlling constraint. Replenishment time must also be removed from the operating window whenever the machine cannot serve vehicles while recharging.
Door Energy offers several mobile storage and charging configurations, and replenishment arrangements differ by model. Some systems can use DC charging infrastructure or an AC distribution source. For the autonomous product, calculate replenishment from the confirmed input power, efficiency, starting SOC and target SOC; do not copy the refill time of a different Door Energy product.
A straight line between the standby point and a vehicle ignores pillars, one-way aisles, walls, ramps, gates, pedestrian zones and temporary obstructions. The correct distance is the route the robot can legally and safely travel. At feasibility stage, multiply the straight-line radius by a route factor.
Actual one-way route: Straight-line distance x route factor
| Parking layout | Suggested route factor |
| Open single-level layout | 1.2-1.4 |
| Single level with many pillars / turns | 1.4-1.6 |
| Several connected parking zones | 1.5-1.8 |
| Multi-level garage | 1.7-2.2 |
| Route crosses controlled gates | Measure on site |
The MCP-D’s published maximum speed is 10 km/h, but a planning model should use the average safe task speed rather than the maximum. For an indoor or mixed-traffic parking environment, an initial assumption of 1.5-3 km/h is more useful until a supervised route test confirms the value.
At an average speed of 2 km/h and a route factor of 1.5, a 100 m straight-line radius becomes a 150 m one-way route. The round trip takes about nine minutes. If the radius increases to 200 m, the route becomes 300 m each way and the round trip rises to about 18 minutes.
| Straight-line radius | One-way route at 1.5x | Round-trip time at 2 km/h |
| 50 m | 75 m | 4.5 min |
| 80 m | 120 m | 7.2 min |
| 100 m | 150 m | 9.0 min |
| 150 m | 225 m | 13.5 min |
| 200 m | 300 m | 18.0 min |
If charging, connection and administration require 39 minutes, increasing the radius from 100 to 200 m raises the full cycle from roughly 48 to 57 minutes. Theoretical throughput falls by about 16%. A larger coverage map may therefore produce lower service quality and fewer completed requests.
| Demand intensity | Requests per day | Suggested radius | Illustrative response target |
| Low | 4 or fewer | 150-200 m | 15-25 min |
| Moderate | 5-8 | 100-150 m | 10-20 min |
| High | 9-12 | 60-100 m | 8-15 min |
| Dispatch-critical fleet | Shift-based | 50-80 m | 5-10 min |
| Multi-level garage | Zone-based | 60-120 m per zone | Validate by floor |
Multi-level facilities should normally be divided by floor or operational zone. A single geometric radius is too optimistic when the machine must use ramps, pass access controls or navigate different traffic patterns. Door Energy can use the site plan as the first input, but the final radius should be verified through an actual route survey.
Assume 85% occupancy, an 18% EV share, a 25% daily request rate and a 1.1 peak factor. The model produces 7.57 requests per day. At 22 kWh per request, daily energy demand is approximately 167 kWh. One unit can be evaluated for the initial phase if the schedule includes a suitable replenishment window and the service radius remains close to 100-120 m. Expansion should be triggered when demand regularly exceeds eight tasks or departure-time performance begins to deteriorate.
With 70% occupancy, 25% EV share, a 35% request rate and a 1.2 peak factor, expected demand reaches 23.52 tasks per day. At 22 kWh per request, the facility requires about 517 kWh daily. One machine is clearly insufficient even though it might physically reach the full parking area. A practical initial concept is three service zones with approximately three units, subject to the site’s actual replenishment arrangement and peak-hour distribution.
At 90% occupancy, 20% EV share and a 15% request rate, the model produces 6.48 tasks. If the average top-up is 15 kWh, daily energy demand is about 97 kWh. Long dwell time gives the dispatcher flexibility to work through the queue overnight. One unit may be suitable for the first phase, although the operating plan needs either a short replenishment opportunity or enough reserve to avoid ending the shift with unfinished tasks.
Now assume 90% occupancy, 75% EV share, a 30% request rate and a 1.1 shift factor. Expected demand is 17.82 tasks. At 30 kWh each, the depot requires approximately 535 kWh per day. Despite having fewer spaces than the other examples, it needs far more charging capacity. Three or more units, scheduled replenishment and dispatch-priority rules may be necessary.
| Project | Spaces | Tasks / day | Energy / day | Initial interpretation |
| Office campus | 180 | 7.6 | 167 kWh | 1 unit; reserve expansion |
| Retail facility | 320 | 23.5 | 517 kWh | About 3 zones / units |
| Residential parking | 240 | 6.5 | 97 kWh | 1 unit with refill window |
| Logistics depot | 80 | 17.8 | 535 kWh | 3+ units or shift redesign |
The operating process should remain simple for the driver while the scheduling platform manages the complexity behind the scenes. A typical Door Energy autonomous charging workflow contains five steps:
1. Charging request. The driver, parking platform or fleet dispatcher submits a request with the vehicle location and required departure time.
2. System location. The platform uses the parking-space map and sensor information to confirm the target position.
3. Autonomous travel. The machine plans a route and moves to the vehicle while monitoring the surrounding environment.
4. Charging. A robotic arm completes the connection when the project supports automated coupling, or an operator performs manual plug-in. Charging begins after communication and safety checks.
5. Task completion. After the requested energy is delivered, the system disconnects and assigns the unit to the next vehicle, standby point or replenishment location.
A queue based only on request time can charge a vehicle that will remain parked all day while delaying a low-SOC vehicle leaving in 40 minutes. The scheduler should consider departure time, present SOC, requested energy, task criticality and the robot’s remaining energy. Emergency or dispatch-critical tasks receive the highest priority; long-stay vehicles can be shifted to quieter periods.
| Priority | Request type | Suggested rule |
| P1 | Emergency / dispatch-critical | Immediate service |
| P2 | Departure within 60 minutes | Move ahead of flexible tasks |
| P3 | Low-SOC vehicle | Rank by operational threshold |
| P4 | Standard reservation | Serve by promised window |
| P5 | Long-stay vehicle | Schedule in a low-demand period |
| System | Robot energy below task requirement | Replenish before dispatch |
A two-to-four-week Mobile EV Charger pilot can replace assumptions with site evidence. Record request acceptance, average and 95th-percentile waiting time, kWh delivered, task duration, empty travel, replenishment time, manual intervention and failure reasons. The 95th percentile matters because an acceptable average can hide a small group of very late tasks.
| Pilot metric | Why it matters |
| Task completion rate | Shows whether promised service is consistently delivered |
| Average response time | Tests whether the service radius is realistic |
| 95th-percentile wait | Reveals poor performance during busy periods |
| Average kWh per task | Replaces the energy assumption with actual demand |
| Empty-travel share | Improves standby-point and route design |
| Replenishment-time share | Tests whether input power is sufficient |
| Manual intervention rate | Quantifies labor and compatibility issues |
| Failure reason | Separates vehicle, connector, network and route problems |
For broader project planning, buyers can review Door Energy product configurations and application cases. Door Energy also develops mobile storage and charging systems for roadside response, commercial vehicles and outdoor industrial applications. Depending on the selected configuration, the wider product range can support OCPP, CCS1/CCS2, high-power DC charging and AC loads such as pumps, lighting or electric construction equipment. Those capabilities should be evaluated separately from the autonomous parking model rather than mixed into a single capacity claim.
A1. In many early-stage projects, one unit can be evaluated against 80-250 parking spaces within an 80-150 m straight-line radius. Low-demand, long-dwell facilities may support a larger zone; high-turnover or dispatch-critical sites usually need a smaller one.
A2. No. The rating is the maximum output ceiling. Vehicle limits, battery temperature, SOC and the charging curve determine actual average power. Capacity models should use measured or conservative average power.
A3. A reasonable initial range is approximately 6-10 tasks per day, depending on energy per request, route length, connection method, operating hours and replenishment. A project delivering 40-50 kWh per vehicle will complete fewer tasks than one providing 15-22 kWh top-ups.
A4. It may be acceptable in a low-demand, simple, single-level facility. For moderate or high demand, 80-150 m is usually a better starting range because longer routes reduce throughput and increase waiting time.
A5. Add capacity when routine demand exceeds about 80-85% of stable capability, the 95th-percentile wait exceeds the service promise, or replenishment can no longer fit inside the operating schedule. Critical fleets may also require an N+1 reserve.
A6. No. A robotic arm can reduce routine labor when parking accuracy and vehicle-interface compatibility are controlled. Manual plug-in can simplify deployment, but staff response time must be included in every task cycle.
A7. Simultaneous service depends on the confirmed output-port and power configuration. Do not assume multi-vehicle charging in the model. If only one vehicle can connect, use a sequential task queue.
A8. The MCP-D product information states IP55 protection and an operating range of -20 to 65 C. A site assessment is still required for standing water, snow, ice, ramp conditions, local rules and the specific connection process.
A9. It is better suited to dispersed or uncertain demand, sites with expensive cabling, flexible parking allocation and on-demand service. Fixed charging may be preferable for vehicles that always occupy assigned bays and require large, predictable daily energy. Hybrid deployment can use both.
A10. Provide the parking plan, number of spaces, number and type of EVs, occupancy, expected requests, average energy per request, dwell time, departure deadlines, connector standard, operating hours and available replenishment power.
The useful answer to “How many spaces can one Mobile EV Charger cover?” is not a single universal number. For most feasibility studies, 80-250 spaces, an 80-150 m service radius and approximately 6-10 daily tasks provide a sensible starting envelope. The final result must be calculated from demand, energy and time.
The correct sequence is straightforward: count the spaces, measure occupancy, estimate EV share, forecast the request rate, define the energy target, model the full task cycle, trace the real route and then determine the number of machines. Reversing that sequence creates two common mistakes. Too little capacity produces missed departure deadlines; too much capacity lowers utilization and weakens the business case.
Door Energy’s MCP-D combines 105 kWh of onboard storage, up to 100 kW DC charging, OCPP 1.6J communication and L4 autonomous movement in a platform intended to bring charging service to parked vehicles. Its value is not simply that it moves. The operational advantage comes from sharing charging capacity across ordinary parking spaces and scheduling each task according to energy need and departure time.
Before final procurement, carry out a route survey and a two-to-four-week pilot. Replace assumed energy, travel and connection values with measured results. That evidence will show whether the site needs a wider service zone, a different standby location, faster replenishment, another unit or a revised service promise.
For a project-specific assessment, send Door Energy the parking layout, EV mix, daily vehicle turnover, average required energy and available power source. The team can use those inputs to discuss a suitable configuration, service radius and replenishment strategy. Contact Door Energy to begin the evaluation.
This article is an educational planning guide. International market and charging-session reference points are drawn from public information published by the International Energy Agency and the U.S. Department of Energy. Product specifications are based on the Door Energy MCP-D product page available when this guide was prepared. All coverage ranges, route factors and utilization allowances are planning assumptions that require confirmation through site survey, local regulation review and project testing.