Knowledge HUB

Insights from battery experts

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Insights

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BMS vs Analytics

The lack of a standardized approach on how State of Health (SoH) should be calculated and the fact that on-board battery management systems (BMS) alone are not sufficient in assessing battery safety are highlighting the need for battery analytics.
solar energy storage solar panels snow mountains

5 Steps to Maximize the Value of Battery Energy Storage Systems

This article walks you through some of the most common steps when considering the deployment and operation of a battery storage system, and shows you the power of data monitoring, smart algorithms, and simulations to maximize the economic return of battery energy storage systems throughout their lifetime across multiple revenue streams.
Electric trucks battery analytics

Electric vehicle safety and reliability

Battery safety and reliability are essential to OEMs and operators. Why is battery intelligence needed to maintain a safe and reliable operation? Why is a battery management system not enough? The article explains the complexity of EV batteries.

Energy storage: an overview of our content

Get an overview of our energy content, covering topics like safety and warranty in the energy sector, deployment and operations of energy storage systems, and general use cases of battery energy storage systems.

Battery development: an overview of our content

Find an overview of topics related to battery development in this article. Read about battery technologies, the battery industry, and battery simulation models.
EV Battery

Electric vehicles and fleet management: an overview of our content

Batteries are the future of mobility. Want to learn more about electric vehicles and their batteries? We have got you covered on topics like battery safety, operation and management of batteries, battery development, and residual values. Get an overview of our content pieces.
Improving BESS performance, availability and safety

Improve the safety, availability and performance of your battery energy storage systems

Battery energy storage systems (known as BESS or ESS) are essential for accelerating the shift towards green energy. They are now an integral part of the electricity grid across the globe, meaning that their safety, availability and performance is more important than ever.
EV safety

Safeguard electric vehicle fleets with battery analytics

There are a complex variety of causes of reliability and safety problems with electric vehicle batteries. In this whitepaper, we explore EV battery safety and reliability concerns, potential causes of issues, and how battery analytics can help overcome these challenges.
TWAICE battery lab

A new generation of aging models for lithium-ion batteries

The latest version of the TWAICE simulation model, Version 9, introduces the first steps towards a new generation of battery simulation models: The physics-motivated semi-empirical aging models.

Protect aftersales profits: Start with accurate and reliable insights into battery health

In this whitepaper, we discuss the core challenges caused by battery aging, how these affect aftersales departments across the industry, and how battery analytics can help OEMs overcome these challenges.
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Battery Energy Storage System Safety: How to Avoid the Worst Case Scenario

The lithium-ion battery market is growing fast, meaning safety incidents are likely to get more and more frequent. Battery analytics helps companies reduce the risk of battery energy storage system fires.
electric bus charging in city

E-bus charging strategies

What kind of e-bus charging strategies exist and what is their impact on battery health and aging? This whitepaper provides these answers and shows how battery analytics can help operators make data-driven, informed decisions regarding the best charging strategies for their e-bus fleets.
Holding battery component in front of people

Mechanistic calendar aging model for lithium-ion batteries

In this work we present a novel mechanistic calendar aging model for a commercial lithium-ion cell with NCA cathode and silicon-graphite anode. The mechanistic calendar aging model is a semi-empirical aging model that is parameterized on component states of health, instead of capacity.
TWAICE battery research in front of computer

Measurement Approaches for Thermal Impedance Spectroscopy of Li-ion Batteries

Battery performance, lifetime and safety are highly dependent on temperature. With the recent high demand for power capabilities, heat management has become increasingly relevant.
TWAICE battery electric vehicle

Evaluation of transmission losses of various battery electric vehicles

Transmission losses in battery electric vehicles have compared to internal combustion engine powertrains a larger share in the total energy consumption and play therefore a major role. In this paper, three simulation models of the Institute of Automotive Engineering are presented.
cell testing in the TWAICE battery research center

Modeling capacity fade of li-ion batteries

Aging models are fundamental tools to optimize the application of lithium-ion batteries. In this work, we show that the CAP-method models capacity fade more accurately when applied to dynamic cyclic aging tests with periodically changing mean state-of-charge, depth-of-discharge, ambient temperature and discharge rates for a commercial NCA cell with a silicon-doped graphite anode.
TWAICE testing simulation, Batteriemodell-Bibliothek

Combining EIS and time-domain data

This work proposes a method to combine time-domain and frequency-domain measurement data for parameterization of RC elements by exploiting the full potential of the distribution of relaxation times (DRT).
lithium ion battery labs module, batteriemodell|

Quantifiability of Cell-to-Cell Variations

Motivated by the question of why impedance variation is consistently reported to be higher than the variation of other parameters, we show that measuring inherent parameter variations caused by production tolerances is superimposed by effects of an imperfect measurement setup.