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

Solar panels in front of an energy storage systems

How energy storage systems are used

As related costs decrease and deployment options increase, more and more, energy storage systems (ESS) are becoming essential for sustainable energy production. The ability to store energy as well as supply it makes the technology suitable for multiple use cases. Understanding all the possible use cases for ESS makes that attractiveness even clearer.
Electric fleet management

In-life mobility solutions

Most fleet managers in the public sector, and operators of larger commercial fleets are now opting for electric vehicles. Nevertheless, there are still some concerns about this new technology regarding battery failure costs. This is when battery analytics becomes a key-value driver to unleash the full potential of battery-powered fleets.
Energy Storage Systems

De-risk deployment & operations of energy storage systems

On average battery energy storage systems are only available 82% of the time. Many issues however can already be detected before deployment, in the commissioning phase. The article explains the advantages of digital commissioning, like a quicker analysis and more detailed insights into KPIs and potential manufacturing failures.
Green Tech Battery

Battery industry 2023: More sustainability, safety and independence

Battery industry predictions for 2023 by Dr. Matthias Simolka, Product Manager Energy Solutions at TWAICE.
TWAICE Model Library

Improve battery system design with battery simulation models

Batteries are a key technology in the transition to carbon-free mobility. When it comes to designing battery systems for electric products, batteries must meet certain requirements that must still be met after years of operation, in order to avoid jeopardizing the intended business case and damaging companies. TWAICE's simulation models help engineers make the right decisions fast when designing a battery system, leading to reduced risks, improved reliability, and faster time to market.
wind energy storage on fields

De-risk your BESS projects by keeping track of warranty conditions

What are performance warranties and why are they important in the design, operation and bankability of battery energy storage systems projects? This article answers these questions and shows how our TWAICE Warranty Tracker can minimize risks and ensure a successful business case.
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.
Lithium-ion battery cells degradation

Modeling Particle Versus SEI Cracking in Lithium-Ion Battery Degradation

This work identifies and systematically compares three different SEI interaction theories, and applies them to experimental degradation data from a commercial lithium-ion cell. It shows that SEI delamination without any cracking of the active particles, and SEI microcracking, where cycling only affects SEI growth during the cycle itself, are both unlikely candidates.
BESS failure analysis

Insights from EPRI's BESS failure incident database

This report is intended to address the failure mode analysis gap by developing a classification system that is practical for both technical and non-technical stakeholders.
Battery production and testing

Non-destructive electrode potential and open-circuit voltage aging estimation for lithium-ion batteries

In this publication we extend a state-of-the-art electrode open circuit potential model for blend electrodes and inhomogeneous lithiation. We introduce a bi-level optimization algorithm to estimate the open parameters of the electrode model using measurements conducted on the full-cell level with state-of-the-art testing equipment.
Battery development

Mechanistic cycle aging model for the open-circuit voltage curve of lithium-ion batteries

Cycling lithium-ion batteries causes capacity fade, but also changes the shape of the open-circuit voltage (OCV) curve, due to loss of active material (LAM) and loss of lithium inventory (LLI). To model this change, we recently proposed a novel empirical calendar aging model that is parameterized on component states of health (s) instead of capacity fade only.
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.