Systems study · energy, power and operations
Dual-battery truck systems
A swappable main battery and a fixed reserve can change how a truck uses its stored energy. Compare the complete operating cycle, inspect the blocks behind it, and separate a proposed benefit from the evidence needed to establish it.
Illustrative engineering study. Generic vehicle and pack assumptions; no measured validation of the announced hardware. Fleet cost calculation is the next stage.
Route and components · one native simulation
Replay the full route and its electrical circuit together
Select a condition and system. One recorded timeline drives contactor feedback, current and power flow, battery SOC and temperature. The vehicle circuit carries pack, contact and DC-link state between intervals; switching uses short native transient windows.
Loading coupled route evidence.
System-level route and service contracts
This is an authored direct-contactor circuit with an energized departure bus, passive pack cooling and declared limits. During a loaded transfer, the native protection latches traction off if the DC bus reaches the declared minimum: 300 V in these cases. Each transfer has a maximum 3 s native observation window; closure requires measured voltage matching and actual contact feedback. These are model assumptions, not production hardware specifications. Distance follows the requested route profile while demand is served; vehicle acceleration and friction-brake blending are not modeled. Grid energy and total losses include returned-pack recovery at the station, including work after the vehicle finishes; vehicle pack-energy and balance figures cover onboard intervals only. Returned inventory has separate pack identities and availability times. The earlier ideal-dispatch campaign below remains a separate reference.
Recorded ideal-dispatch reference campaign
Where each system helps — and where it reaches a limit
Compare all seven systems under light and heavy payloads, cold and hot ambient conditions, longer and faster routes, climbs and descents. Each condition starts a fresh model and keeps the same requested duty across the seven architectures. Select a result to open its complete connected model and trace.
Loading campaign evidence.
Across the campaign: completed duties and limits for each system
| System | Completed | Conditions completed | Conditions incomplete or unavailable |
|---|
What this condition shows
| System | Duty status | Distance (km) | Grid (kWh) | Vehicle delay (min) | Unmet (kWh) | Recovery after service (min) | Sampled route temperature peak, main / reserve (°C) | Recorded limit or stop |
|---|
These are authored scenarios, not measured road trials. Incomplete cases retain their stop events and executed distance. Downhill cases show requested versus accepted regeneration. The route model omits friction-brake blending, so completing a descent does not verify braking capability. A blocked charge interval ends the current replenishment attempt: this scheduler does not wait for passive cooling and retry. Hot-reserve readiness failures therefore identify a limit of the present service policy, not a permanent inability to repeat a trip. Temperature peaks cover route samples only; station charging and peaks between samples are outside that measure. Grid energy includes declared station inventory recovery. Fleet cost modeling remains a separate next stage.
Complete operational model → subsystem → native blocks
Explore every compared system
Each system below has its own connected model, assumptions and recorded example results. Open a subsystem’s interfaces, then inspect the exact main or reserve battery network used by that scenario. Use the comparison controls further down to change the duty and recalculate.
Loading complete model
Model and run identity
Calculated effects
Trade-offs
Loading the connected model.
All subsystems and their interfaces
| Subsystem | Model location | Ports | View |
|---|
Complete system connection table
| From | To | Contract / units | Model binding |
|---|
Actual parameters of this system
| Parameter | Value | Model location |
|---|
Example route result
Recorded service, dispatch and failure events
| Time | Event | Recorded details |
|---|
Inside this system’s battery subsystem
Native battery model
The electrical and thermal blocks below are generated from the selected system’s actual pack parameters and initial state. Their independent departure load check exposes charge depletion, heating, power delivery and limits. The component player below the diagram shows these recorded states for this exact battery model. It does not replay the reserve’s later takeover state. The route model above also includes source dispatch, travel, station service and recharge.
Exact pack inputs and source identity
Scope and limits of this complete model
Additional physical experiments · native calculation
Explore transfer and converter alternatives
These separate experiments test possible contactor, reserve and converter solutions. Their circuits are not assigned to the route systems above, which use their declared source-dispatch model. Choose an experiment, inspect its connected blocks, edit inputs and run it to see the physical effects.
Loading examples
Effects and trade-offs
The Design link opens the named experiment. Download and import the model to retain your edited inputs and connections.
Calculated effects
Same route · same requested payload
Compare system choices
Start with a prepared comparison, then change the operating conditions. A reserve must have enough power for the load and enough energy to reach the next service point. Its charge and temperature persist between trips.
| System | Distance | Unmet energy | Grid energy | Service delay | Reserve after service | Duty complete |
|---|
Energy and delay totals cover the executed portion of the duty. Unmet energy is the recorded power shortfall before the run stops, rather than the energy required for all remaining travel. Reserve SOC is the final state after recorded service.
Follow one system through the route
Service and handover events
| Time | Event | Details |
|---|
Run identity, assumptions and model limits
Problem → solution → effect → trade-off
What each change can do
Use more of the main pack
Problem: an operational return reserve leaves energy in a pack that is about to be swapped.
Solution: provide a separately available reserve and lower the main-pack return threshold.
Effect to test: additional main-pack energy used before service, completed duty and minimum reserve margin.
Trade-off: more hardware, mass and maintenance; the reserve may be unavailable when cold, depleted or power-limited.
Keep the reserve ready
Problem: a fixed reserve is not refreshed by swapping the main pack.
Solution: track its own state, temperature and recharge opportunity across trips.
Effect to test: repeat-trip completion and replenishment time, including finite site power and ready-pack inventory.
Trade-off: an initial-trip advantage may disappear if reserve recovery cannot keep up with the duty.
Match power to the duty
Problem: usable kWh does not guarantee enough traction power on a grade.
Solution: separate charge and discharge limits, cold derating and source supervision.
Effect to test: requested versus delivered power, unmet energy and pack temperature.
Trade-off: higher-power or cold-capable variants require characterized cells, cooling and control. The variants here are declared assumptions.
Keep the comparison fair
Compare the single-main baseline with a policy-only change to isolate the effect of the return threshold. Compare the dual system with an equal-energy fixed pack to distinguish architecture from added capacity. Retain the same requested route, payload, ambient condition and service requirements. Report incomplete duty alongside energy use: a system that travels less must not look more efficient merely because it delivered less work.
As nominal capacity arithmetic, 95% of 432 kWh is 410.4 kWh and 70% is 302.4 kWh: a difference of 108 kWh, or about 35.7% relative to the latter. The operating-window difference is 25 percentage points. This illustration assumes a 100% starting SOC; it is not an exact terminal-energy result. The default study instead starts at 95% SOC and uses a 5% dual-system return threshold, a 90% charge-SOC window. Modeled terminal energy also depends on voltage, the selected state window, power and temperature limits, and losses. Neither calculation establishes a measured range increase or higher cell energy density. Reserve energy is accounted separately and is not counted again after it has served the load.
A 3C charging rating does not establish reserve discharge power or full charge time. Source handover must also be checked against bus voltage, current limits, protection, contactor or converter behavior and an explicit transient time scale. This route study does not verify the announced millisecond switching claim.
Reusable Design model
Inspect the system blocks
The article uses the same source modules and pack solver as Design. Select a subsystem to see its inputs, outputs, affected metrics and evidence boundary.
What the results establish
Loading execution qualification.
The announced topology, reserve discharge envelope, switching sequence and production thermal maps are not supplied here. The study therefore evaluates explicitly declared architectures. A passed numerical check means the stated equations and accounting agree; it does not validate a production truck or prove uninterrupted handover.
| Claim or design choice | Question for the model | Evidence status |
|---|
Study catalog · Prepared execution evidence · Claim and source bindings · Exact runtime identity · Download corresponding source
Moving components, with a path toward measured behavior
The physical experiment player follows native recorded samples. A contactor blade moves when its calculated actual closed feedback changes; command and feedback are shown separately. Scrub through opening delay, precharge, closure, refusal or fault. The initial DC link in the handover experiment is already charged: this shows a transfer after startup.
The route campaign uses ideal source dispatch. Its main/reserve selection can be replayed, but it does not contain a physical contactor sequence. Connecting the two time scales requires carrying the route battery states into a fast electrical window and returning its losses, limits and faults to the route model.
| Model layer | Available now | What is needed for closer agreement with hardware |
|---|---|---|
| Contactors and precharge | Commands, delayed actual feedback, finite resistance, precharge resistor, link capacitance, readiness gates and timeout/fault states. | Actual topology, contactor timing and resistance, DC-link capacitance and impedance, controller sequences, synchronized command/feedback/current/voltage measurements. Bounce, arc and certified breaking behavior are not modeled. |
| Battery and cooling | SOC-dependent voltage, current limits, bulk heating/cooling and temperature gates. The campaign’s default resistance temperature coefficient is zero. | Measured voltage, resistance and allowable-current maps across SOC, temperature and health; cell/module temperature gradients, cooling control, thermal wait-and-retry service logic and calibrated ageing. A cold ambient run alone does not establish chemistry performance. |
| Vehicle and route | Architecture mass, payload, speed, grade, acceleration, regeneration and auxiliary demand in declared route segments. | Measured route/driver traces, motor and inverter efficiency maps, traction and friction-brake blending, realistic auxiliaries and cooling loads. |
| System integration and validation | Repeatable native runs, model/run identities, accounting checks, fault experiments and component-state playback. | Route-to-fast-window checkpoint integration; time-step convergence, fault campaigns, calibration against measurements and separate held-out validation traces. |
Fleet costs: next stage
This study exports energy flows, charging and service time, pack usage, payload distance and asset state. A future cost model must add tariffs, battery ownership or lease terms, station capital and operating costs, staffing, downtime valuation and residual value. No fleet cost saving, total ownership cost or profitability is calculated here.
References and scope
- CATL-issued announcement, 20 October 2026. Identifies the reported pack capacities, architecture and claimed operating benefits. Its claims are separately marked in this study.
- A. Brooker, J. Gonder, L. Wang, E. Wood, S. Lopp and L. Ramroth (2015). FASTSim: A Model to Estimate Vehicle Efficiency, Cost and Performance. SAE Technical Paper 2015-01-0973. DOI · National-laboratory publication record. Supports the use of declared vehicle and duty inputs in reduced powertrain analysis; no numerical parameters or validation results from that model are reused.
- Y. Preger, H. M. Barkholtz, A. Fresquez, D. L. Campbell, B. W. Juba, J. Román-Kustas, S. R. Ferreira and B. Chalamala (2020). Degradation of Commercial Lithium-Ion Cells as a Function of Chemistry and Cycling Conditions. Journal of The Electrochemical Society, 167, 120532. DOI · Research record. Shows why chemistry and operating conditions belong in a durability assessment. Its commercial-cell experiments do not establish the life of this proposed system; no lifetime fit is taken from the paper.
Source records reviewed on 29 October 2026. Explanations, interfaces, scenario construction and comparison presentation are authored for Lemonergy. Manufacturer identities are retained to identify the source announcement.