The toolbox
The full capability set of the engineer-led depot twin, grouped by what you're deciding. It's physics-based, grounded in peer-reviewed engineering science rather than rules of thumb or vendor guesswork. Every capability is capacity-level and directional, and every number traces to a named assumption. The free feasibility check is live now; the rest is part of the engineer-led twin, built with you and owned by you.
Every run answers three questions, separately, never merged: Capability: can each vehicle physically do its shift? Delivery: under your electrical limits, did every vehicle get its energy? Charging Capacity: does any node exceed its rating, and when?
Digital twins come in three broad shapes: facility twins (BIM-based models of already-built buildings), operational twins (real-time IoT-fed models of running infrastructure), and process-simulation twins (models of a repeated workflow that let you change parameters and see the impact before committing).
BEV Ready is the third kind, applied to EV depot planning. The workflow it models is your depot's charging day, at 15-minute resolution. You change parameters (fleet size, vehicle types, charger count and power, service capacity, tariff) and see feasibility and cost. It's a planning tool, not an operational system: it doesn't connect to your chargers or run your depot. It answers the questions that come before you buy any of that.
A fast first-pass screen for a depot: energy demand, peak load, the likely utility service tier, and a rough cost, in minutes rather than a multi-week study.
Not: a detailed design or a commitment-grade number. It tells you whether a depot is worth pursuing.
A 15-minute-resolution charging-load profile across the worst plausible day, managed vs. unmanaged, with per-node feasibility against the site's electrical limits, showing where and when a plan would breach service capacity.
Not: a billing-grade or stamped study. It's capacity-level, single-day, and directional.
Charging follows a real constant-current / constant-voltage curve, including the taper as each battery nears full. A charger's effective throughput therefore reflects the physics, not a flat rate that overstates how fast the fleet tops up.
Not: a manufacturer-specific charge model; it's a representative CC-CV curve, capacity-level and directional.
Models a grid-import limit that varies through the day (low- and high-power periods) and shows where storage bridges the low-power window so charging continues through it. Capacity-level and directional, not a billing-grade study.
Not: a go/no-go. The conservative worst-day feasibility verdict assumes a depleted battery and doesn't count the bridge. It benefits only sites where the constrained connection would otherwise strand energy.
A multi-day representative week that generates a feasible charge schedule: which bus, which charger, when, at what power. It meets every departure under the service limit, with conservative day-over-day battery carryover. Every assignment traces to a rule.
Not: an operational commitment or a control plan. It's a capacity-level, directional reference.
One click loads a cold-service-day preset (higher driving energy, stretched charge window) or a hot-day preset (cooling load). Every value labeled, sourced, and editable.
Not: hidden buffers. Conservative presets that only ever raise demand, shown and adjustable.
Shows the key verdict as a band, not a dot, by re-running the model across the plausible range of your highest-leverage assumptions. The spread is real, traced to named ranges.
Not: a fabricated ±. The band is the model's own output across sourced assumption ranges.
Idle buses discharge their spare energy (only what sits above each bus's own next-shift reserve) to shave the depot's evening peak. Round-trip losses are counted; no free energy.
Not: ever at the expense of a bus's own route. A bus that would strand is refused, not counted. Vehicle-to-load, not V2G.
Honest scope
Is: surplus-only discharge, refuses-to-strand, round-trip losses counted on delivered energy, peak-shave of the depot's own load. Isn't: grid export, V2G arbitrage, a revenue model, a battery-vs-tariff optimizer.
Model a no-grid or grid-capped window and a relocatable power unit that carries the depot through it. If the sources can't cover it, the window reads infeasible, surfaced not hidden.
Not: a live control integration. Charge curtailment is modeled (response latency and power floors respected), not a live-control hookup.
Feasibility across a range of battery sizes for the operating week. It's a decision space you read and choose from, each size feasibility-checked against the frozen engine.
Not: an opaque “the size.” You pick; the tool shows the consequence.
A directional estimate of the monthly demand-charge dollars at the modeled peak, from sourced, dated utility rates, with a diversity/coincidence option. When no rate resolves, it says so rather than guessing.
Not: a guaranteed utility bill; time-of-use and ratchet structures are simplified.
Shows the demand-charge saving a battery would deliver on the modeled day, and a directional storage business case.
Not: a sizing recommendation; resilience is described qualitatively, never priced.
A 20-year EV-vs-ICE lifecycle view covering NPV, payback, and TCO. It's calculator-first: enter your own quotes and rates, or use clearly labeled directional defaults. Every figure traces to a named assumption and is confidence-labeled.
Not: a guaranteed bill, a financed quote, or investment advice.
A handful of fixed configurations (stay-ICE, grid + chargers, + solar, + storage, + both), ranked by 20-year NPV and feasibility-checked, surfacing the trade-offs.
Not: an auto-pick or optimizer. It doesn't size or schedule for you, and an infeasible scenario never outranks a feasible one; cost never overrides physics.
The value of shaving that peak: avoided demand charges and mobile-unit fuel, set against battery cycle cost, as a directional range with every figure named to its tariff and dated rate. When a rate won't resolve, it says so rather than guessing.
Not: a bill, a financed quote, or investment advice. The battery cycle cost is always counted, so an upside-only number is impossible.
Electrify in stages (25% → 50% → 100%) and see which grid upgrade (cost and lead-time) lands at which stage.
Not: a recommended schedule. It's your phasing against sourced ranges, never a quote.
The scenario and configuration outputs reframed as a distribution of outcomes and a size-and-mix decision space: the trade-offs laid out, not a single answer.
Not: an auto-pick or optimizer. It presents the spread and the options; the call stays yours.
Emissions
Compare a depot's diesel-era baseline against its electrified operating profile and report avoided tCO₂e, keyed to the grid emission factor for the depot's province or region. Grid import is floored at zero per interval; export intervals don't generate negative emissions. If the region isn't set, the figure withholds rather than falling back to a national average. The figure inherits the day-type selected in the UI (worst-cold or typical), same as SOH derating.
Re-runs the worst day with chargers removed to show which buses get stranded and how much service you lose. Plus a backup-duration screen: how long your parked fleet + battery carry a critical load through an outage.
Not: a live control system. A capacity-level, read-only resilience check; it only ever surfaces more risk, never less.
As batteries age, usable capacity fades. Sweeps your fleet across its service life and marks the year each bus crosses from likely → borderline → hard.
Not: a recommended replacement year. A directional, typical-day pre-screen. Run the worst-day verdict for the hard number.
Set the assumptions yourself (energy per shift, battery basis, utility rates, derates) and sweep them to see what actually moves the verdict. The model is yours to interrogate, not a black box you take on faith.
Not: a fixed set of vendor defaults. Every input is visible, editable, and traceable.
A print-ready, defensible summary of what the depot needs and why: the modeled day, demand-charge exposure, the financial memo, and an assumption ledger where every figure traces to its source. Built to justify a service-capacity review with your utility and a licensed engineer. Avoided-emissions arithmetic: worst-cold or typical, keyed to the depot's province.
Not: a stamped engineering study or a financial offer.
Once a site is operating, log observed periods and see how reality tracked the modeled day, with drift and longitudinal trend.
Not: live or operational control.
Roll individual depots up into a fleet-wide view with multi-year phasing, giving one picture of the whole transition to plan and defend across sites.
Not: a substitute for the per-depot model; it aggregates the same directional, capacity-level runs.
The pilot mode runs alongside the frozen feasibility engine. It never edits it, and a stripped-back pilot run must agree with the worst-day verdict. Same discipline, longer horizon.
Not: a second opinion that can quietly disagree with the screen. The two are reconciled by construction.
In development
A future capability that would let the fleet export surplus energy to the grid or arbitrage it against tariffs, on top of today's on-site V2L peak-shaving. Not modeled in this version.
Honest scope
It's a capacity-level, directional model. The feasibility screen models a single worst-plausible day; the operating-week view simulates a multi-day representative week. Both are directional, sharp enough to decide service upgrades, BESS sizing, and charger counts. It is not a billing-grade, stamped, or "optimal" plan. The financials (20-year TCO, NPV, payback) are directional, named-assumption estimates you can re-run with your own inputs, not a guaranteed bill or investment advice. A BEV Ready engineer builds and validates it with you, then hands you the keys. You keep a living model that gets more accurate the longer it's used. It feeds your engineer, utility, and board; it doesn't replace the licensed PE who stamps the design.
Run a directional screen of your depot in minutes: energy demand, peak load, the service tier you'll likely need, and a rough cost. Then start the engineer-led twin with our team.