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

TWAICE Vision 2022 battery dark lights

TWAICE Vision Conference Report

TWAICE hosted a conference about the importance of software in a battery-driven future. Speakers from leading companies in the electric vehicle, energy and battery industries discussed its challenges. A conference report now highlights the main findings of the event.
electric car charging at night

Three e-mobility trends 2022

The importance of e-mobility to sustainability and environmental awareness continues to grow. Some of the trends that will be emerging for this year include battery-drive at the cutting edge, image change for batteries, and second life batteries enabled by software analytics.
Solar panel energy storage

Predictive battery analytics in the energy sector

Battery storage is a fundamental part of the energy sector. Batteries, however, are complex systems. Deriving the maximum profit from them without incurring any additional risk is the overarching goal of most energy operators. This is where battery analytics can help.
Electric Bus charging optimization

E-Bus Battery Optimization

The e-bus market is already moving fast in 2021. Established bus manufacturers are setting the pace. E-bus manufacturers are currently facing a plethora of questions and uncertainties. Major challenges include the development of the highly complex batteries, warranty management, sustainable fleet management and the issue of battery reuse and recycling.
Battery Automotive electric vehicle recalls

Electric Vehicle Recalls

Numerous recent recalls showed how much risk is associated with the most important competent of the emission-free mobility. The battery is a highly complex piece of technology that must be tightly analyzed not only during the development but also during operation.
traffic future of mobility

Future of Mobility

Even though batteries are a controversial topic, most manufacturers and legislators rely on battery electric vehicles because of its advantages over other alternatives. This article examines why batteries are the future of mobility and play a key role for renewable energies.
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.