Electric vehiclesMobility

Full EV vehicle

The battery pack you sized becomes the car you drive — a complete electric vehicle over the WLTP cycle: drive cycle, traction motor, regen, the battery over the cycle, thermal, and the numbers that sell a car — range, consumption, and 0–100.

DjiniousLabModelling & simulation

A PMSM traction-motor efficiency map — torque against speed coloured by efficiency, with a high-efficiency island peaking near 97% inside the torque-speed envelope

WLTP range (60 kWh): 374 kmWLTP range (60 kWh)
kWh/100km consumption: 15.2kWh/100km consumption
0–100 km/h: 6.67 s0–100 km/h
energy from regen: 10.7%energy from regen
pack rise over WLTP: 7.0 Kpack rise over WLTP
design notebooks: 10design notebooks

From battery pack to the car you drive.

The EV battery program sized the pack. This one drives it. A complete electric vehicle — traction motor, single-speed driveline, regenerative braking, vehicle dynamics, and the pack from the battery program — run over the WLTP drive cycle, on one coupled electro-mechanical-thermal model. Out come the numbers a buyer and an engineer both care about: range, consumption, acceleration, and how hot the pack gets doing it.

One coupled chain, the cycle as input.

The WLTP speed trace is the input, and the model runs backward through the drivetrain: speed and acceleration set the tractive force (aerodynamic, rolling, inertia), the wheels demand power through the motor's efficiency map, the driveline and regen split it, and that lands on the battery as a constant-power load. The pack — the same equivalent-circuit cell from the battery program — sags on acceleration, recovers on regen, depletes its state of charge, and heats up, all from one set of coupled equations. The battery you sized at the cell level is now answering vehicle-level questions.

A PMSM efficiency map: torque versus speed, coloured by efficiency, with a constant-torque region, a field-weakening envelope, and a ~97% efficiency island — The traction motor as an efficiency map: a constant-torque region up to base speed, a field-weakening envelope above it, and the high-efficiency island (~97%) the controller tries to keep the operating point inside. This map — not a detailed field-oriented-control model — is what consumption integration over a drive cycle actually needs.

Pack voltage and state of charge over the WLTP cycle — voltage sagging on acceleration and lifting on regen while SoC trends down — The battery over the WLTP cycle: state of charge trending down while pack voltage sags on every acceleration and lifts on every regen event. The constant-power load model — the physical root of P = V·I against the cell's OCV(SoC) — is what makes that sag come out right.

Range is an accounting problem.

Consumption is just energy in minus energy recovered, divided by distance. The model breaks the WLTP energy into where it actually goes — aerodynamic drag, rolling resistance, powertrain losses, accessories — and how much regen claws back (10.7% over the cycle, 52% of the braking kinetic energy). That ledger gives 15.2 kWh/100km and a 374 km range, and it shows exactly which term to attack: at 130 km/h cruise, aerodynamic drag dominates and consumption climbs to 21.4 kWh/100km — the range-anxiety curve, quantified.

A donut chart of WLTP net energy: aerodynamic 41%, rolling 32%, powertrain loss 11%, auxiliary 8%, kinetic net-of-regen 8% — Where the consumed energy goes over WLTP: aerodynamic drag and rolling resistance dominate, powertrain losses and accessories take their cut, and the kinetic term is small because regen recovers most of it. This is the chart that tells you whether to chase a slipperier body, lower-rolling tyres, or a more efficient motor.

The range-anxiety chart: steady-cruise consumption rising with speed, and the range falling as the inverse, annotated at highway speeds — The range-anxiety chart: hold a steady cruise and consumption rises with the square of speed while range falls as its inverse. The same coupled model that gives the WLTP number gives the honest highway number — and shows what +5 kW of HVAC does to it.

A full-throttle launch: vehicle speed rising to 100 km/h in 6.67 seconds, traction-limited then power-limited — Performance from the same model: a full-throttle launch reaches 100 km/h in 6.67 s — traction-limited off the line, then power-limited as the motor runs out of envelope. Range and acceleration trade against the same pack and motor, and here they're both just outputs.

Every spec is a number you can re-run.

The sign-off notebook re-derives each requirement from first principles over the same cycle the program drives.

Result

WLTP range: 374 km
WLTP consumption: 15.2 kWh/100km
0–100 km/h: 6.67 s
Pack temperature rise: 7.0 K
Requirements verified: 6 / 6

Requirement

WLTP range: ≥ 350 km
WLTP consumption: within target
0–100 km/h: within target
Pack temperature rise: within limit
Requirements verified: PASS

Backward-facing, design-grade.

The model is backward-facing and quasi-static — the cycle is the input, not the output of a driver chasing it — which is the industry-standard way to get range and consumption, and it avoids a controller and stiffness for no fidelity gain. The motor is an efficiency map rather than a field-oriented-control PDE, the battery is the equivalent-circuit surrogate from the pack program, the thermal model is lumped, and the WLTP profile is a faithful approximation (the official second-by-second trace is proprietary). It is exactly the fidelity vehicle concept and sizing needs first — battery and motor sizing, range and consumption, the regen and thermal budget — on your own numbers, before a full dynamic co-simulation. And because the pack is shared, the cell-level work and the vehicle-level work never drift apart.