Lead the Charge in Battery Innovation
Perfect battery performance isn’t a luxury – it’s a necessity. You need intelligence, speed, and efficiency to meet today’s expectations for driving range and charging time. But conventional testing slows you down: Long state-of-health (SOH) determinations drag early development. Late-stage validation with physical prototypes delays SOP. And on-road battery health remains a blind spot. Shift left testing – to virtualized, data-driven validation that delivers answers before problems arise. From cell development to pack integration to in-use, accelerate every step with simulation and automation. As global competition intensifies and the battery market grows 20 % annually, cutting prototype reliance and scaling insight is essential. With AVL on your side, you merge fleet data, predictive models, and engineering expertise – to optimize battery management system (BMS) strategies, extend lifetime, and move faster. From lab to road – precise, preventative, and cost-effective.
SOH Prediction, Fast and Scalable
Battery Pack Validation Without Vehicle Prototypes
Fleet-Wide Battery Health Visibility
Longer Driving Range, Shorter Charging Time
Ageing Root Causes & KPIs, Fully Transparent
Earlier Insights, Lower Costs
Predict Cell Ageing With Precision – Let’s Release
Speed up SOH determination by acting smarter, not slower. Outdated test campaigns stretch over a year – tying up testbeds, overloading climate chambers, and stalling timelines. Each factor influencing battery ageing – from charge/discharge cycles over temperature to resting and mechanical stress – requires months of isolated testing. Even OEMs re-run supplier tests to verify cell ageing. Validation comes to a standstill, capacity stays occupied, and time-to-market slips. But why waste time? Train machine learning models on early cycles to detect patterns between fast- and slow-ageing cells. Let algorithms learn degradation behavior and accurately predict the remaining 20-40 % of the SOH curve using active design of experiments (DoE) strategies. With smart parameter variation and optimized test sequencing, you reduce valuable time, gain insights earlier, and free up resources – driving progress while others are still testing.
Validate Battery Packs in the Lab – Let’s Release
Cut the wait, catch the risk: Validating battery packs in physical vehicles may reflect true conditions – but it comes far too late. Discovering issues at this stage puts SOP timelines at risk and increases cost for corrective actions. Shift validation to the battery testbed instead. With battery-in-the-loop and complete vehicle simulation, you mirror real-world loads, thermal dynamics, and driver behavior with full automation. The battery pack responds like it's on the road, while you stay in control of every parameter. Simulate range, stress performance, and extreme temperatures. Evaluate SOx values such as state-of-charge (SOC) under realistic driving conditions and refine your strategies early. Run ageing predictions, thermal stress scenarios, and full performance tests at vehicle level – even before the first prototype exists. No late-stage surprises. No costly rework. No thermal runaways. Just sharper decisions, more flexibility and enhanced safety.
Forecast SOx Across Fleets – Let’s Release
Stop guessing the condition of the battery. Predicting SOx during operation is often inconsistent – misleading the BMS and undermining warranty events and maintenance planning. Why? Because in-vehicle systems only see one battery in a vehicle. Without broader data context, values fluctuate erratically and lose meaning. Move from fragmented readings to cloud-based intelligence supported by connected BEVs and centralized data analytics. By aggregating field data from entire fleets, you can create robust SOx prediction models that feed optimized strategies directly into the BMS. AI methods such as long short-term memory (LSTM) and transfer learning combine lab and field knowledge to increase prediction accuracy. Federated Learning ensures data protection while continuously improving model performance across global fleets. You get early warnings of anomalies, reliable lifetime planning, and precise SOx visibility – not based on hypotheses, but on structured findings. And with root cause analysis, you can quantify what’s really causing battery performance degradation – and what you can do about it.
AVL Software Solutions – Built for the Future
You know the challenge. We bring the tools. AVL's modular software toolchain supports you throughout all stages of e-Mobility engineering.
AVL CAMEO 5™ unlocks a new maturity level of calibration and validation in automotive software testing.
AVL Data Analytics™ is a cloud-first software solution built for the needs of today's automotive engineers, driving powerful data insights and effective actions at scale.
AVL Virtual Studio isn't just another software product; it's a comprehensive virtual testing experience aimed at addressing the complex challenges faced by modern test systems.
EVolve Mobility Webinar Series
Faster, Smarter, and Safer EV Development
Reduce Development Time. Increase Quality. Accelerate Innovation.
The EVolve Mobility Webinar Series delivers 5 focused deep dives on how to cut testing time, boost battery performance, and speed up software releases — all with smart, integrated solutions for the future of electric mobility.
Gerald Sammer
Principal Business Development Manager