Batteries are a key component of electric vehicles, but they need to be replaced after a certain amount of use. This usually happens once the battery has lost 20–30 % of its capacity and power, which directly impacts the range, performance, and safety of the vehicle. Our toolchain for battery lifetime prediction includes battery testing, battery aging simulations and vehicle fleet tracking. It provides everything you need to determine the state of health, the impact of driving behavior, optimization potential for your operation strategy, and when a battery can no longer be used in a vehicle.
A battery must be durable but powerful, able to withstand high temperatures and constant loads. Battery monitoring is a crucial part of the battery system and safety. It can help you prevent any unwanted events, such as thermal runaway or blow-up. While you can measure voltage, power output and temperature, there are reactions within cells that can lead to a different electrical behavior. Monitoring the battery and its cells - individually and in the overall network - is essential to making accurate predictions about failure and remaining useful lifetime.
State-of-Health (SoH)
SoH is key to drawing conclusions regarding remaining value and lifetime. How to accurately determine the SoH of batteries?
Driving Behavior
Driving behavior has significant impact on battery life. How to identify behavior prolonging battery life and behavior leading to battery degradation?
Operation Strategy
What is the best operation strategy? Knowing the impact of driving behavior, you can optimize for battery health and lifetime.
End of Life
At what point can a battery be no longer used in a vehicle and needs to be replaced?
Our battery lifetime prediction toolchain includes battery testing, battery aging simulation and vehicle fleet tracking. This will enable you to gain an accurate picture of the impact of driving behavior on battery ageing and to draw conclusions for an optimal operation strategy. With our incredibly secure data transfer system, Device.CONNECT™, your data is transferred from the vehicles on the road to a customized analytics platform. The platform can link battery models and data from manufacturing, testing and fleets, analyze it and provide visualizations of the results.
The solution is tailored to your specific needs in terms of what kind of analytics and tools you require as well as the monitoring content and modelling approaches.
Drivers of Battery Aging
It allows you to understand the main drivers of battery ageing.
Optimizing the Operation Strategy
It enables operation strategy optimization to increase fleet driving range and lifetime, and to avoid routes, conditions and behaviors that drive ageing.
Predicting the End of Life
Battery life can be balanced across the fleet, and predictions about when and why battery life will come to an end can be made.
Replacing Batteries and Second Life
Fleet operators can plan battery replacement costs as well as the battery’s second life value and improve the vehicle warranty process.
Battery lifetime prediction answers some of the most pressing questions in e-mobility: current state of health, effects of usage and remaining useful battery life.
As part of our AVL Battery Lifecycle Management approach, battery lifetime prediction is a first step on our way towards a circular economy.
– Alwin Tuschkan, Project Manager IODP, AVL
Battery Lifetime Prediction for Electric Vehicle Fleets Solution Sheet
Comprehensive information and technical details.
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