Insights from battery experts

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.

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.

The automotive sector’s transition to green mobility is challenging the bus operators across the world. That was the case of a major operator of electric buses in the Netherlands, who reached out to ViriCiti and TWAICE regarding our Battery Health Solution to integrate data-driven decision making focused on batteries, to avoid timely and costly warranty discussions.

What is the potential impact of Battery Health Reports (BHR) on remarketing success of the battery electric vehicle (BEV)? Besides age and mileage, driver profile has a major impact on how long a battery lasts. In the absence of documentation of how a driver has treated the battery, residual value formation remains below its full potential.

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.

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

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.

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.

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).

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.