Heavy-Payload AMR Battery Sizing A Three-Shift Energy and Charging Workbook

A factory can finish a successful AMR demonstration with less energy in every battery than it had at the start. If the same deficit repeats during the night shift, a convincing demonstration becomes an unsustainable production schedule. The question for a three-shift plant is whether the fleet can complete its transport work, preserve its operating reserve and return to a repeatable energy state.

AMR battery sizing therefore requires two linked calculations: enough usable energy between effective charging events, and enough replenishment across the repeating production cycle. Charger access, battery condition and the timing of material demand determine whether those calculations remain valid in service.

The existing guide to AMR opportunity charging and fleet availability explains the strategy choices. This workbook turns those principles into a numerical example that production engineers, procurement teams and integrators can challenge together.

Start with three conditions the operating plan must satisfy

A credible plan for three-shift AMR operation must satisfy three conditions at the same time. First, each robot must retain enough energy to finish its assigned work and reach an available charger. Second, the repeated schedule must replace the energy it consumes. Third, enough robots must remain available to serve production while others charge.

These conditions answer different questions. A larger battery can help a robot bridge a long interval between charging events. It cannot indefinitely compensate for a daily energy deficit. Additional chargers can create more replenishment capacity, but they do not help if all vehicles must remain in production during the only usable charging windows.

Catalog runtime is useful only with its conditions attached. The official MiR1350 specifications list active operation of 6 hours 45 minutes at maximum payload and 9 hours 50 minutes without payload, while noting that local conditions and application setup affect specifications. Those are product-specific figures, not guarantees for the hypothetical system in this article.

The practical starting point is a measured mission profile. Capture the load, route, speed restrictions, stops, attachments, waiting behavior and ambient conditions that actually define the application. Then ask the supplier to show which measurements support its proposed operating schedule.

Worksheet 1: account for every hour and every energy boundary

An AMR duty cycle analysis should begin with mutually exclusive operating states. If propulsion, computers and a top module are already included in a measured whole-vehicle power value, adding them again as separate loads overstates consumption. Conversely, a drivetrain-only estimate can omit meaningful application energy.

Use battery-side, whole-vehicle measurements for discharge demand wherever possible. Keep the facility's AC electricity consumption separate: it includes charger losses and potentially other loads. For replenishment, use the net increase in recoverable battery energy, after charging losses and onboard consumption during charging. This prevents gross electrical input from being mistaken for energy available to later missions.

The example allocates six hours and forty minutes to non-charging states and eighty minutes to effective charging. Baseline travel to and from charging locations is already included in the travel rows. Baseline setup and waiting are included in their respective non-charging states. There is no additional invisible period outside the eight-hour shift.

The power values are averages within each state, not peak electrical ratings. Motor, contactor, cable and battery power capability still require separate checks against short-duration loads. A battery can contain sufficient energy while being unable to support the required instantaneous demand.

For the calculation below, each four-hour block contains half of every non-charging state, followed by forty minutes of effective charging. It therefore consumes 3.00 kWh before recovering 3.00 kWh. Real production will rarely divide so neatly; this deliberate simplification makes the energy logic visible before route variability is introduced.

Worksheet 2: translate pack capacity into a usable operating window

A heavy-payload AMR battery should be selected against usable energy at the design condition, not nominal capacity alone. Specify how capacity is measured, the intended service condition and the manufacturer-approved operating limits. Ampere-hours alone are insufficient for comparing packs with different voltages.

Nominal voltage multiplied by ampere-hours gives an approximate nominal watt-hour value. It does not establish how much energy the complete application can use between its approved upper and lower boundaries. State of charge, or SOC, is also not automatically a linear measure of recoverable energy across every chemistry, temperature and discharge profile.

For a transparent AMR battery capacity calculation, this example makes three assumptions: a 12.00 kWh nominal pack, 80% retained capacity at the selected design condition, and an approved operating energy window equal to 70% of that retained capacity. These percentages are scenario inputs, not standard end-of-life or SOC requirements.

Operating energy window = 12.00 kWh × 0.80 × 0.70 = 6.72 kWh

The 70% factor is an assumed fraction of measured recoverable energy. It is not an instruction to subtract two dashboard SOC percentages and treat the result as an exact energy measurement. In a real project, replace the factor with a supplier-supported usable-energy map for the selected temperature, load and battery condition.

Define Q as recoverable energy remaining above the approved lower boundary. In this example, Q ranges from zero to 6.72 kWh. Separately reserve 0.60 kWh for operational contingencies, leaving 6.12 kWh for planned discharge. The reserve should ultimately be justified by recovery travel, expected uncertainty and the consequences of an interrupted mission.

With one normal 3.00 kWh work block, Q falls from 6.72 to 3.72 kWh. If one charging event is missed, two work blocks require 6.00 kWh and leave 0.72 kWh. That exceeds the illustrative reserve by only 0.12 kWh. A pack that appears generous during normal operation has very little additional allowance under this missed-charge case.

The same assumptions give a nominal capacity threshold of (6.00 + 0.60) ÷ (0.80 × 0.70), or approximately 11.79 kWh, for bridging those two blocks. The proposed 12.00 kWh pack barely clears that arithmetic threshold. Selection still requires evidence about uncertainty, permitted configuration and power capability.

Worksheet 3: follow the battery through a complete production day

A daily energy total conceals the sequence of withdrawals and replenishment. Evaluate the energy before each charging event as well as after it. The battery must remain inside its permitted operating window throughout the schedule, not simply show an acceptable value at midnight.

Energy after work = energy before work − work-block consumption
Energy after charging = the smaller of the upper energy limit and energy after work + net recovered energy

If energy after work would fall below the operational reserve, the assignment requires revision before execution. Energy that a charger could theoretically deliver beyond the upper limit cannot be saved as a credit for a later shortfall.

The robot consumes 18.00 kWh and recovers 18.00 kWh over twenty-four hours. It finishes at its starting energy state, so this idealized cycle can repeat. That is a necessary result, but it offers no scheduled surplus for recovering from an energy deficit. Production release needs a recovery arrangement as well as a balanced baseline.

This table is a single-robot energy trace, not a command for every fleet member to charge simultaneously. Its charging periods must fit the production service requirement. The separate guide to AMR fleet capacity planning addresses the number of mission-capable robots needed during demand peaks.

For a multi-day or weekly production pattern, carry the actual final state into the next period. A weekend recharge can legitimately belong to a repeating weekly plan if production permits it. Resetting every simulated shift to a full battery without allocating that recharge time cannot demonstrate continuous operation.

Break the model before approving it

Failure case A: the booked window contains only twenty charging minutes

An AMR charging time calculation must distinguish time away from missions from time delivering useful energy. Suppose a forty-minute booking contains six minutes of approach travel, seven minutes of queueing, four minutes of docking and communication, and three minutes of departure. Only twenty minutes remain for effective charging.

That booking cannot replace the forty effective minutes required by the baseline. At the assumed average net rate of 4.50 kW, twenty minutes recovers only 1.50 kWh. Holding work-block consumption at 3.00 kWh, energy after successive charging events falls to 5.22, 3.72 and 2.22 kWh. The fourth work block would cross the 0.60 kWh reserve before completing its planned consumption.

This comparison isolates the lost charging time. Additional energy from extra travel or queueing would need to be added and could worsen the result. The corrective action might be a longer protected window, a different charger location or a revised dispatch schedule. Calling the same booking “opportunity charging” does not change its energy contribution.

Failure case B: one complete charging session is missed

If the first 3.00 kWh recharge is missed, the robot reaches the end of the second work block with Q at 0.72 kWh. The next normal recharge raises Q to 3.72 kWh. Subsequent normal blocks then cycle between 0.72 and 3.72 kWh rather than restoring the original baseline.

The missed session creates a 3.00 kWh energy debt. At the same validated average replenishment rate, recovering it requires forty additional effective charging minutes. Those minutes must be scheduled when the battery has room to accept the energy, while production still has sufficient transport capacity.

An additional 0.20 kWh of consumption during a later work block, before its recharge, would lower that block's minimum from 0.72 to 0.52 kWh and breach the assumed reserve. This is why surviving one missed session is different from recovering operating resilience afterward.

Failure case C: charging power is lower than the planning average

The 4.50 kW figure is an assumed average net recovery rate across the intended operating window. It is not a claim that a charger delivers constant power. For a measured session, sum net recovered energy over the actual time intervals and compare the total with the next mission's requirement.

The EnerSys NexSys iON owner's manual, particularly its charging discussion on printed pages 14–15, explains that charging current varies with SOC, battery temperature, charger temperature and charger specifications. It also requires approved charging equipment. These are product-family instructions illustrating why the actual battery–charger combination must be evaluated.

If average net recovery in this example falls to 3.75 kW, each forty-minute session returns 2.50 kWh. Six sessions replace 15.00 kWh against 18.00 kWh consumed: a 3.00 kWh daily deficit. A larger pack can delay the resulting restriction but cannot make this unchanged schedule sustainable.

Scale the result to charging ports, deadlines and electrical supply

AMR charging station sizing starts with charging demand expressed in port-hours. Eight robots following the baseline each need four effective charging hours per day. Their combined requirement is thirty-two port-hours, provided the assumed recovery rate remains available.

Now assume one independently usable charging port can provide twenty schedulable energy-transfer hours per day after allowing for non-transfer occupancy and service restrictions. Twenty hours is a project assumption. It is not an industry utilization rule, and it must be supported by the proposed operating schedule.

In the two-port configuration, losing one port leaves a modeled replenishment shortfall of 12 × 4.50 = 54.00 kWh per day. That is missing battery-energy recovery capacity, not a measurement of electricity bought from the grid. Installing a third independent port restores the daily arithmetic under this specific outage assumption.

The daily result is only a lower-bound capacity check. If all eight robots retain the identical forty-minute windows shown earlier, even three ports cannot serve them simultaneously. Staggered schedules must be tested against each vehicle's energy deadline, travel time and the minimum number of robots required in production.

Two docks sharing one power cabinet may also share a bottleneck or failure mode. Confirm concurrent output, power allocation and recovery behavior. Facility engineers must evaluate AC demand using the actual charger input specifications and site conditions; multiplying the example's net battery-recovery rate by the number of docks is not an electrical installation design.

The site's AMR site survey checklist supports location and infrastructure checks. Use AMR simulation validation to examine queues and competing deadlines, with this ledger providing a transparent check on the model's energy accounting.

Make battery aging a procurement condition with measurable consequences

AMR battery state of health matters because the fleet must operate beyond the first demonstration. Ask what the reported health value represents: measured capacity, an algorithmic estimate or another diagnostic. Establish the test conditions and the relationship between that value and the usable energy required by the application.

The example's 80% retained-capacity assumption must become either a supported design condition or a clearly identified uncertainty. Do not apply a further aging reduction if the supplier's tested usable-energy figure already includes the same degradation. Equally, avoid assuming that a displayed health percentage captures every temperature or power limitation.

Procurement should request the approved battery, charger and firmware combination, accessible operating data, capacity-verification method, replacement criteria and support responsibilities. Warranty coverage should be checked against the actual duty cycle and charging practice. A generic cycle-life figure does not describe the project's future available energy by itself.

For safety evidence, the official scope of IEC 62619:2022 covers industrial secondary lithium cells and batteries and includes AGVs among its motive applications. Relevant battery evidence does not establish complete AMR application acceptance or prove that a three-shift energy schedule will work.

If the model fails, compare specific corrective options. A larger approved pack addresses storage between charging opportunities. More usable charging time addresses replenishment. Another independently supplied port addresses resource contention. Additional fleet capacity may free vehicles for charging. Each proposal should identify the constraint it removes and the new assumptions it introduces.

Turn the workbook into an energy acceptance record

An AMR charging acceptance test should demonstrate the repeated production pattern and the agreed recovery cases. Define the load mix, routes, initial energy distribution, battery condition and environmental range before testing. Starting with every robot fully charged can conceal weaknesses if normal operations begin with mixed states.

Record synchronized timestamps, robot and battery identifiers, missions, payloads, SOC, available battery-health data, pack voltage and current, temperature, charger requests, arrival times, effective charging start and stop, and charging interruptions. Retain the raw data behind summary dashboards so unexplained changes can be investigated.

Close the record with four project-specific results:

1. Production service: completed transport demand and missed deadlines while charging activity occurred.
2. Energy minimum: the lowest verified usable-energy estimate and its distance from the agreed operating reserve, including measurement uncertainty.
3. Cycle closure: whether the final energy state supports the next repeated production period without an undocumented recharge.
4. Recovery: how the system responds to the selected missed-window or charger-outage case and how long it takes to restore its normal reserve.

Reconcile measurements at their declared boundaries. Battery-terminal electrical energy, modeled stored energy and facility AC energy are related but not identical. Agree how efficiency, estimator uncertainty and data gaps are treated before deciding whether a discrepancy is acceptable.

The broader AMR operational acceptance guide addresses system readiness. The energy record adds a specific release question: can the accepted configuration reproduce its production service and energy state under the conditions the buyer is actually purchasing?

Focused FAQ

How large should a battery be for three-shift production?

There is no universal capacity. Calculate the energy required between feasible charging events, add a justified operating reserve, and evaluate the result against measured usable capacity at the design condition. Then verify that the repeated schedule replenishes the energy consumed.

Can one battery support a full twenty-four-hour production day?

Potentially, if approved charging opportunities replenish it while the fleet continues serving production. The example recovers energy six times during the day. Three-shift factory operation does not require every individual robot to perform missions continuously for twenty-four hours.

Why does a larger battery not always fix charging problems?

Capacity stores energy; charging replenishes it. Increasing storage can bridge longer gaps or absorb one disruption, but a repeated daily deficit will still deplete that larger store. Correct the replenishment or workload imbalance as well as evaluating capacity.

Is charger rated power enough to calculate charging time?

No. Use the validated recovery profile for the permitted battery–charger combination and intended operating window. Account for charging losses, onboard loads, temperature effects and time spent travelling, queueing or establishing the charging connection.

Does passing the daily port-hours calculation prove the fleet will work?

No. Daily capacity can be sufficient while individual robots miss their charging deadlines. Validate concurrent demand, access routes, shared power limits and the minimum production fleet throughout the schedule, including the agreed outage condition.

What should a buyer request before approving the proposal?

Request a complete duty-cycle ledger, supported usable-energy assumptions, charging-session measurements, a feasible fleet schedule and an acceptance record covering production service, energy minima, cycle closure and recovery. Those deliverables make the proposed operating capability reviewable.

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