Knowledge HUB

Insights from battery experts

Explore the latest trends, research papers, blog posts and more. Join us as we cover hot topics, debate the future of tech and share trending stories.

Insights

battery pack assembly line

Battery Technology

Batteries are highly complex electrochemical systems with different cell formats and chemistries being used. The processes inside the battery also deserve particular attention.
Electric Car market dynamics

EV Market Dynamics

The electrification of mobility is accelerating quickly and turning the automotive industry and other major industries upside down. With electrification the focus shifts away from the engine towards the batteries.
Lithium ion battery technology

Why do lithium-ion batteries age, and how to slow it down?

Electric vehicle batteries are costly and sensitive parts, and their performance depends on numerous factors like frequency of charge and discharge, the charging system, driving habits, and external temperature. Until now, it was almost impossible for developers or users of batteries to make any reliable analysis or statement about the current state of the device. However, this information can be now delivered by the digital twin created by TWAICE.
battery development testing lab

Battery development

This article looks at the development of batteries and how virtual testing and software solutions can accelerate and improve the development of battery-powered products while keeping the time to market low.
EV safety

Enhancing EV battery safety and reliability with predictive analytics

AI-enabled analytics let you analyze, monitor, and forecast battery performance across vehicles or fleets, adding an extra layer of safety by identifying issues other systems miss and providing centralized access to all relevant battery insights.
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.
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.
Wind turbines over forest electricity

Energy Storage Analytics

Battery storage systems are an essential component of the energy sector. However, they are complex systems that require special attention. The primary goal of storage owners is to maximize the profit possible from the storage system without taking on additional risk. This is where battery analytics comes into play.
Battery cell testing in the TWAICE battery lab for battery modeling

Approaches to battery modeling

Batteries are complex systems whose operation is determined by a variety of factors, making long term projections a challenge. However, it is possible to understand the future conduct of these systems by building models that mimic their behavior and leverage the computational power to perform the required calculations.
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.
impedance of lithium-ion batteries research paper

Impedance Research Paper

Continuous impedance monitoring provides significant insights into the aging status of a battery. However, the on-line determination of battery impedance parameter for its low-frequency part is a challenging task. This paper provides an algorithm for its determination, which features a novel approach to quantifying the impedance caused by diffusion processes at low frequencies.