Lithium-Ion Battery Pack Design Simulation for Electric Cars and Passenger EVs

Designing a Passenger EV Battery Pack with Simulation: From Targets to Design Report

Introduction

For an electric car, the battery pack decides range, charging time, safety, weight and warranty cost. It is also the part where mistakes are most expensive. An undersized BMS, a hot cell in the middle of a module or a weak insulation barrier usually shows up only after prototypes are built and tested.

Simulation moves those discoveries earlier. The IST Li-ion Battery Simulator is a browser-based workbench that takes a passenger EV pack from application targets through sizing, cell modelling, thermal, BMS, electrical, safety and life analysis, and ends with a design report. Nothing needs to be installed on your computer.

This post walks through how that workflow applies to a car-class battery pack.

What Makes a Passenger EV Pack Different?

Compared with a scooter or e-rickshaw pack, a car pack has to deal with:

• Higher voltage and energy: Class B voltage levels bring isolation, pre-charge, contactor and fuse requirements.
• Demanding drive cycles: Cars are expected to cope with urban, highway and aggressive driving, and range claims are tested on standard cycles.
• Fast charging and hot climates: Both push cell temperatures up.
• Long warranties: Owners and OEMs think in years and lakhs of kilometres, so ageing prediction matters.
• Stricter safety expectations: Thermal propagation, protection response times and standards compliance can block a release.

For Indian passenger vehicles, the simulator maps this to the M/N-category standard AIS-038 Rev 2. It also checks against UN R100, UN 38.3 and IEC 62619, with cell tests to IS 16893.

Why Passenger EVs Need Simulation-Led Design

Compared with smaller vehicles, a car pack faces:

• High power and energy: Large currents during acceleration and DC fast charging create heat in cells, busbars and connectors.
• Long life expectations: Owners expect eight years or more of dependable performance, and warranties usually reflect that.
• Structural role: Many pack enclosures are part of the vehicle’s crash structure and underbody protection.
• Regulatory pressure: Safety rules are tightening worldwide, particularly around thermal runaway.
• Cost and mass trade-offs: Every extra kilogram of enclosure, cooling hardware or insulation costs range and money.
• Wide climate range: The same pack must work in a Delhi summer and a Scandinavian winter.

Simulation allows engineers to examine all of these together, early, and cheaply.

The Regulatory Picture: Safety Is Now a Design Driver

The most visible example is China’s updated traction battery standard. GB 38031-2025 and GB 18384-2025 entered into force on 1 July 2026, and battery systems must no longer present a risk of fire or explosion, even in the event of thermal runaway. That is a big step up, because the previous version only required a warning signal five minutes before a potential fire or explosion. The new rules also add tests such as bottom impact, and fast-charging cycle safety testing, requiring batteries to withstand 300 fast-charging cycles without fire or explosion during a subsequent short-circuit test.

Industry estimates suggest compliance could raise battery system costs by 15 to 20 per cent, which makes it even more important to find efficient designs rather than simply adding protective material everywhere. Requirements vary by region and change over time, so always confirm the current version with your certification body.

This is where simulation earns its place. Physical thermal propagation and impact tests are destructive and expensive, so teams use simulation to narrow down candidate designs before committing to hardware.

Step 1: Start with the Application, Not the Cell

Every design begins in Define Application. For a car you enter the application type (BEV), the voltage window, energy capacity, continuous and peak discharge power, charge power, system mass, ambient range, IP target, cooling method, weight budget and the standards you must satisfy.

These targets are not just a form. They drive the pack checks, the vehicle model for drive cycles, the usage profile for ageing and the header of the final report. The guide’s advice is worth repeating: fill the voltage and power targets carefully, because the most useful output of pack configuration is the list of targets your chosen cell and BMS cannot meet.

Step 2: Pick the Cell and BMS from a Real Database

The simulator draws every part from an importable database with seven libraries: cells, BMS, BTMS, master/module PCBs, busbars, cold plates and other parts. You can import parts as .dat files (single files or a zip), add them through a form or export to CSV.

For a passenger EV, cell selection comes down to a few questions:

• Chemistry: LFP is the safest and longest-lived. NMC and NCA offer higher energy density, and LTO gives very long life at lower voltage.
• Format: Fewer, larger prismatic cells mean fewer welds and a simpler BMS. Smaller cylindrical cells need more parallel strings but give better fault tolerance.
• DCIR: This drives heat generation, voltage sag and cooling need.
• Temperature limits and cycle life: These feed directly into the ageing and warranty models.

On the BMS side, the simulator checks that the series range covers your Ns, that OVP and UVP sit inside the cell window, that continuous and peak over-current limits match the pack’s needs, and that the BMS over-temperature trip does not exceed the cell’s limit.

Step 3: Size the Pack and Check It Against the Targets

In Pack Configuration you enter Ns, Np and the number of modules, or let the simulator suggest them from your targets. The Generate Cell Model step returns the cell model, a cell-to-BMS check, pack sizing, a pass/warn/fail check against your targets and a standards checklist.

The sizing maths is transparent. Pack voltage is Ns times cell voltage, capacity is Np times cell capacity, and pack resistance is Ns times cell DCIR divided by Np, with a 10% allowance for busbars, welds and contactors.

An illustrative example. Take 120 prismatic LFP cells in series, each 150 Ah, 3.2 V and 0.8 mΩ DCIR (the cell used in the guide’s e-3W walkthrough):

• Nominal voltage: 120 × 3.2 = 384 V
• Energy: 384 V × 150 Ah = 57.6 kWh (about 51.8 kWh usable at 90%)
• Pack resistance: 120 × 0.8 mΩ × 1.10 ≈ 106 mΩ
• Heat at 150 A (1C): I²R ≈ 2.4 kW inside the pack

That last number is why thermal design cannot be an afterthought in a car. Peak power also needs checking at minimum voltage: for a 100 kW peak, the minimum pack voltage of 300 V (120 × 2.5 V) means roughly 333 A, so the cell pulse rating and BMS peak limit must both support that. These figures are only an example, so replace them with your own cell and targets.

Step 4: Model the Cell

The BDS Cell Modeling module builds the cell models the rest of the simulation relies on:

• HPPC-based ECM extraction gives R0 and two RC pairs.
• EIS-based fitting gives ohmic, charge-transfer, CPE and Warburg parameters.
• A reduced-order P2D (SPMe-type) electrochemical solver is benchmarked against PyBaMM’s DFN model, with 0.2–1.7 mV RMS agreement over the tested conditions.
• Joint parameter identification fits electrochemical parameters to a measured voltage trace.

When you don’t have test data yet, the simulator auto-generates inputs from the selected cell, labelled as synthetic. The honest approach is to use these to get moving, then replace them with measured data as soon as you have it.

Step 5: Thermal Analysis and Cooling Design

Thermal work covers several layers:

• Conjugate heat transfer along a coolant channel and coolant flow with pressure drop calculations.
• 3-D cooling simulation for liquid cold plates, forced air or natural convection. It builds a voxel model from the real cell geometry, including anisotropic cell conductivity, gap materials, a thermal interface and an aluminium cold plate. For liquid cooling you set flow rate, channel count, width, height and parallel or serpentine layout. Results include maximum temperature, cell-to-cell ΔT, coolant outlet temperature, pressure drop, pump power and an energy-balance check.
• Thermal imaging live view, an animated eight-module view with a staged cooling controller (off, low, medium, high).

The guide suggests targets of Tmax at or below 45 °C and cell-to-cell ΔT at or below 5 K. One honest note from the guide: this is not a full Navier-Stokes solution. Flow maldistribution and detailed channel shapes still need full CFD or a test, so treat the 3-D cooling card as a way to compare concepts and size the system before detailed work.

Step 6: Thermal Runaway and Propagation

For passenger cars, this is where many designs are won or lost. The propagation module represents a module as a 2-D network of cells with per-cell abuse kinetics for the selected cell, internal short after separator melt, venting and heat transfer through gaps, barriers, busbars and radiation.

You choose the trigger (heater, nail or over-temperature), test SOC, cooling on or off, and the barrier: none, 2 mm air, 1 mm mica, 2 mm aerogel or 3 mm ceramic fibre. The results show how many cells go into runaway, the time between the first and second event, a map of runaway times and an automatic barrier comparison. It also reports a 5-minute proxy, checking whether at least 300 seconds pass before the next cell goes, or whether propagation is avoided entirely.

The practical value is picking the cheapest barrier that stops propagation or buys enough time, then confirming it with a physical propagation test. An ARC-style runaway analysis, calibrated to your cell chemistry and showing the margin to the BMS over-temperature trip, supports this.

Step 7: BMS Design and Drive-Cycle Simulation

The BMS section covers pack circuit behaviour, protection and balancing logic, SOC/SOH estimation (EKF SOC, RLS resistance and an ageing tracker) and a closed-loop drive-cycle simulation with pack, BMS and vehicle model together.

For a passenger EV the relevant cycles include:

The report picks MIDC automatically for four-wheelers, though you can change it. A useful caution from the guide: UDDS, HWFET, US06, WLTC and WMTC are regulatory traces, while MIDC and NEDC are rebuilt from UNECE R83 tables, so use the official ARAI trace for any published range claim.

There is also BMS code generation with SIL and HIL. The simulator generates C code for the protection state machine, current limits, balancing, EKF SOC and CAN messages (with a DBC file), plus software-in-the-loop test vectors. A pass means the generated C reproduces the simulator’s BMS logic at every step. The guide is upfront that the code is template-based, MISRA-oriented and not certified, with no ISO 26262 tool qualification, so it needs review, static analysis and on-target testing. Short-circuit protection must also exist in hardware.

Step 8: Electrical, Circuit and Module Design

For high-voltage car packs, the Circuit Design tab covers:

• MAGNET analysis: Busbar magnetic field and force, eddy-current losses, contactor solenoid pull-in and current sensors.
• HV/LV sizing: Fuse (derated and rounded to a standard rating), busbar cross-section (about 3 A/mm² for copper), pre-charge resistor, minimum isolation (at least 100 Ω/V) and HVIL.
• DFM: Module geometry, tolerance stack-up and joining method for each connection.
• Module wiring diagrams: Series-parallel connections, balancing taps, NTC positions and BMS connection diagrams, with SVG export, 2-D schematics and a 3-D layout with STL export.

Step 9: Ageing, Warranty and Duty Cycles

Because passenger EVs carry long warranties, the life models matter as much as peak performance.

• Calendar and cycle ageing models SEI growth, particle cracking, lithium plating in cold or fast charging and the capacity knee, calibrated so the model reproduces the cell’s datasheet cycle-life rating.
• Warranty prediction takes your warranty terms (years, km, cycles, SOH threshold), usage (km per day, Wh/km, fast-charge share) and Indian city climates, then estimates expected claim rate, SOH at end of warranty and the longest warranty that keeps claims under your target.
• Duty-cycle and BMS-logic verification runs a full day (drive, park, charge, rest) with a fault-injection matrix covering over-charge, over-discharge, over-current, external short, cooling failure, cold charging, open NTC and open pre-charge resistor, each with a detection-latency and pass/fail result.

Step 10: Safety Gates and the Design Report

The Safety & Compliance tab groups checks into electrical performance (capacity, resistance, isolation) and mandatory safety gates (overcharge, short circuit, drop, shock, vibration and protection response time), then rolls them into a release decision, where a failed or un-run gate blocks release.

Finally, Reports runs the whole chain and produces an A4 design report you can download as HTML or save as PDF. It includes the project details, pack configuration, schematics, executive summary, simulation results, standards checklist with evidence, a bill of quantities and a revision and approval section.

What the Simulator Is, and Isn’t

This is worth stating plainly in a blog post because it builds trust. The simulator is a design and screening tool. Pack arithmetic uses standard formulas, while the thermal, abuse, ageing and system models are reduced-order. It does not replace full CFD for detailed cold-plate design, and it does not replace the physical tests needed for AIS-038, AIS-156 or IEC 62619 approval at agencies such as ARAI, ICAT or GARC.

A sensible validation path from the guide:

1. Replace synthetic HPPC, EIS and ARC data with measured data for your chosen cell.
2. Build a prototype module and compare capacity, DCIR and temperatures with the simulation.
3. Run SIL, then HIL, then hardware protection tests on the BMS.
4. Complete cell, pack and transport tests with a testing agency.
5. Start calendar and cycle ageing tests early and refit the life model before committing to a warranty.

Why This Approach Helps Passenger EV Teams

• Faster iteration: Compare cells, Np, BMS options and cooling concepts in hours rather than build cycles.
• Early failure detection: Find unmet power targets, BMS mismatches and thermal hot spots before hardware.
• One shared pack definition: Ns, Np, modules, cell and BMS are entered once and used across every analysis.
• Documentation as a by-product: The report, checklist and BOQ come from the same data as the simulations.
• A path to validation: Results are labelled by confidence, so teams know where to invest in testing.

Conclusion

A passenger EV battery pack is a thermal, electrical, mechanical and software system all at once. The best time to find its weaknesses is before you cut metal. The IST Li-ion Battery Simulator brings sizing, cell modelling, cooling, propagation, BMS logic, ageing and compliance checks into one workflow, helping teams arrive at testing with a better design and fewer surprises.

For electric cars, the battery pack decides how far the vehicle goes, how fast it charges, how safe it is in a crash and how well it holds its value. Simulation lets engineering teams explore thermal, electrical, mechanical and safety behaviour together, and find the best compromise before committing to tooling.

Developing a passenger EV battery pack? Contact us to discuss how simulation can reduce risk, cut cost and speed up your path to certification.

Explore pack design at Academy of EV Technology and follow the step-by-step guide from mission targets to a full design report.