Battery simulation software for battery R&D teams
Faster answers from simulation, fewer cycles on the bench
Battery development still moves at the speed of physical testing. Every design question, every protocol change, every new cell chemistry sends teams back to the cycler for weeks or months of validation. The bottleneck is rarely the physics. It is the gap between experimental data, model parameterization, and repeatable simulation workflows that teams can actually share and trust.
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Ionworks took an open-ended problem and helped us to quickly identify the best course of action, delivering a tailored model of our system.
Ionworks enables our R&D Services customers with tools and insight that support faster development and more predictable outcomes.
Ionworks gives our customers the tools to reduce their development time and cost to implement Iontra Charge Control protocols in their products.
Built by the team behind PyBaMM
Ionworks was founded by the creators and maintainers of PyBaMM, the open-source battery modeling package used across academic research and industry R&D. Ionworks Studio brings that same electrochemical modeling depth into a coordinated web environment built for R&D teams.
The core workflow follows four stages: Measure → Train → Predict → Optimize. Each maps to a concrete step in battery development, from raw cycler data to validated models to optimized designs.
The problem with battery simulation today
Battery R&D teams need software that understands the structure of battery data, models, and experimental protocols. Not a generic simulation platform that promises speed and optimization in the abstract.
The challenge
Fragmented test data. Each cycler vendor uses its own file structure and conventions. Teams lose time reformatting files instead of analyzing results.
What Ionworks does
Structured measurement data. Test data stays linked to its cell, its experimental context, and its provenance. Every downstream analysis starts from a consistent foundation.
The challenge
Parameterization bottlenecks. A DFN or SPMe model is only as useful as its parameters. Connecting experimental data to a model, fitting parameters, and validating the result is manual, error-prone work.
What Ionworks does
Parameterized models. A model (such as DFN or SPMe), a validated parameter set, and a cell specification combined into a single reusable object. Ionworks Studio calls this a parameterized model: the unit of work that makes simulations reproducible.
The challenge
Slow build-test-iterate cycles. A single fast-charge protocol study can tie up cycler channels for weeks. Simulation could answer the same question in minutes.
What Ionworks does
Protocol-driven simulations. Charge at 1C to 4.2V, rest 10 minutes, discharge at C/3. Simulation software should accept the same protocol formats your team already uses: saved, typed, or uploaded from a cycler file.
The challenge
PyBaMM does not operationalize itself. Running a simulation in a notebook is straightforward. Turning that notebook into a repeatable, traceable workflow that a mixed-skill team can use across projects is a different problem entirely.
What Ionworks does
Reproducibility and coordination. When a colleague runs the same parameterized model against the same protocol, the result should match. Immutable models and simulation reuse mean teams can compare results without second-guessing inputs.
How Ionworks works
01
Measure
Ingest and harmonize data from all the major cyclers (Maccor, Neware, Novonix, Arbin, BioLogic, BasyTec, and more). Cycler files are normalized into a consistent format and linked to their cell and experimental context.
02
Train
Fit physics-based models to your experimental data. Select a model type, define the parameters to estimate, and generate a parameterized model your team can trust across studies.
03
Predict
Run protocol simulations against parameterized models before committing cycler time. Evaluate fast-charge strategies, assess lithium plating risk, or compare internal states across cell designs.
04
Optimize
Define engineering targets and search for the best design or protocol. Vary electrode thickness, porosity, loading, or charging strategy while managing degradation and plating constraints.
Use cases
Fast charge protocol optimization
Find faster charging strategies while managing plating risk and capacity retention. Define your constraints and search the protocol space. Results are directly usable as test protocols on the bench.
Battery digital twin workflows
A parameterized model grounded in validated data is the starting point for a digital twin. Run cell-level studies, predict behavior under new conditions, and feed results into system-level decisions.
Battery parameter estimation
Upload cycling data, select the parameters to estimate, and generate a reusable parameterized model. Provenance is built in. The fitting process connects directly to your ingested data.
Battery performance analysis
Compare simulated scenarios against experimental data. Inspect voltage, temperature, and degradation indicators. Every result stays linked to the model and protocol that produced it.
Battery protocol simulation
Evaluate charge-discharge protocols before running long physical tests. Compare variants side by side without tying up test channels.
Battery design optimization
Search design variables against engineering targets like energy density, power, or swelling limits. Every candidate is evaluated with validated physics.
Who we work with
Every battery team hits the same wall eventually: physical testing can’t keep up with the questions their programs need answered. Simulation closes the gap, and looks different depending on the product.
Automotive OEM
Catch battery risk before tooling locks
Challenge
By the time a cell issue shows up in physical validation, supplier contracts and production timelines have already hardened around the wrong assumptions.
Ionworks in action
Cycler data flows in continuously and feeds parameterized models that track each candidate cell. Engineers run duty-cycle simulations in parallel with the test plan, so design questions get answered in days instead of months.
Outcomes
Engineering decisions move earlier. Late-stage redesigns drop. Programs hit their gates on the original timeline.
Drone & Advanced Air Mobility
Push past the bench-tested envelope
Challenge
Real missions cover thermal, altitude, and load conditions that no lab campaign can fully reproduce. Static datasheets stop being useful at the boundaries.
Ionworks in action
Validated physics models extrapolate where empirical data ends. Trade studies sweep range, safety, and lifetime against mission profiles automatically. A search that would take a year of cycler time finishes in an afternoon.
Outcomes
More usable flight time per cell. Defensible operating limits. Faster iteration on the airframe-pack interface.
Materials Development
Connect new chemistry to system impact
Challenge
A promising coin-cell result rarely survives the jump to a real product. Translating material gains into pack-level value takes months of additional testing.
Ionworks in action
Each new dataset slots into a parameterized model and propagates through the same simulation studies the team already trusts. The impact of a coating change or electrolyte tweak on energy, lifetime, and safety shows up in hours.
Outcomes
Faster down-selection between candidate chemistries. Quantified value propositions for partners. Fewer prototype builds before commercial conversations.
Consumer Electronics
De-risk launches without slowing them
Challenge
Battery surprises tend to surface near the end of a product cycle, when the cost of changing anything is at its peak and the launch window is fixed.
Ionworks in action
A living system of record tracks every cell variant, charging profile, and field-relevant aging assumption. As designs mature, the same models predict behavior under realistic usage instead of waiting for survey data.
Outcomes
Predictable battery performance at launch. Smaller late-cycle scope changes. More design freedom for the rest of the product team.
Frequently asked questions
Start with your workflow
If your team is spending more time rebuilding simulations than running them, Ionworks Studio can help. Bring your data, your models, and your protocols.