Predictive Battery Analytics Software

If you’re looking to enhance the modeling capabilities

We specialize in creating custom software solutions for businesses of all sizes. Our team of experienced developers can build software from scratch or work with existing code to create a product that meets your unique needs. Energsoft started as a spin out from University of Washington in 2018 and we collected 500,000 batteries in our databases for modeling and training so far. The chemistries, sizes and architectures are different from our customers.

Create a Cost Function for Fitting

Use a library or write a simple optimization loop to tweak the parameters. Input Measured Data: Import your experimental data from Solatron, Gamry or BioLogic. EIS remains a cornerstone of battery diagnostics and optimization. With the integration of EIS modeling into Energsoft’s analytics platform, battery manufacturers and researchers gain access to cutting-edge tools that enhance reliability, efficiency, and performance prediction. By harnessing AI-powered impedance analysis, Energsoft revolutionizes battery testing, making it faster, more precise, and highly scalable for industrial applications.

Integrate Optimization Algorithms

Provide the flexibility to plug in new model components as needed, allowing you to extend the code for different types of experiments. Measure internal resistance, study charge/discharge cycles, and identify performance-limiting processes. It can help optimize battery designs, understand aging mechanisms, and test materials under various operating conditions

Cloud Solutions

We provide cloud solutions that help businesses streamline their operations and increase productivity. Our team can help you migrate your data to the cloud, optimize your cloud infrastructure, and ensure that your cloud-based applications are running smoothly.

The input data could simply look like this: "Frequency (Hz), Real(Z) (Ohms), Imag(Z) (Ohms)"

Energsoft's platform offers several advantages when handling EIS data, including:

Scalability: Processes vast amounts of impedance data efficiently.
Compatibility: Integrates with major EIS testing instruments.
User-Friendly Interface: Enables easy visualization and interpretation of complex datasets.
Advanced AI-Powered Predictions: Improves battery reliability by forecasting degradation patterns.

Electrochemical Impedance Spectroscopy

EIS is a powerful technique used in battery research and diagnostics to analyze electrochemical systems. By applying a small alternating current (AC) signal over a range of frequencies and measuring the system's response, EIS helps characterize battery behavior, detect faults, and predict battery lifespan. This non-destructive method provides insights into charge transfer resistance, electrolyte conductivity, and other key parameters essential for battery performance assessment.

24/7 Support

We provide 24/7 support to our clients to ensure that their systems are always up and running. Our team of experts is available around the clock to help you with any technical issues that may arise. For instance, if you are monitoring batteries in the field and need remote access to the battery EIS data.

Welcome to Energsoft - EIS Modeling Software

Electrochemical Impedance Spectroscopy

Okay! Let’s pretend your data is like a drawing of a rainbow. You don’t know exactly how the rainbow was made, but you have all the colors in front of you.

Fitting EIS curve

Electrochemical Impedance Spectroscopy

Fitting is like trying to find crayons that can color over your rainbow and make it look the same. You try a red crayon here, a blue crayon there, and a yellow crayon over there until the new rainbow you draw matches the one you already have.

Modelling EIS

Electrochemical Impedance Spectroscopy

Cloud Computing and EIS

Modeling is like figuring out a rule for how the rainbow was drawn in the first place. Maybe you find out it’s drawn in circles with the big red one first, then a smaller orange one, then yellow, and so on. Once you know that rule, you can use it to draw other rainbows or fix any missing pieces in your original rainbow.

Cloud Computing and EIS

So, fitting means finding the best crayons, and modelling means learning how the rainbow was made. Some users find the interface for constructing and fitting equivalent circuits to be less streamlined or intuitive compared to dedicated modeling and fitting software. If the workflow feels cumbersome, it can make the modeling process more time-consuming and less effective.

Testing and QA with EIS

Cloud Computing and EIS

Testing and QA with EIS

We offer comprehensive product testing and quality assurance services to ensure that Energsoft software meets the highest standards for security, accuracy and performance. Our team of experts is dedicated to providing effective testing solutions. More specialized modeling tools often include advanced fitting algorithms, statistical analysis of parameter uncertainty, and the ability to define custom impedance models.

Monitoring Batteries

Cloud Computing and EIS

Testing and QA with EIS

The built-in modeling tools might only support simple equivalent circuits, making it challenging to fit more complex systems that require additional elements, custom components, or advanced modeling techniques. Researchers working on cutting-edge or highly complex electrochemical systems may find these limited options restrictive.

Fitting and EIS Models

EIS Modeling: Understanding Battery Impedance

EIS modeling involves interpreting impedance spectra using equivalent circuit models, which help map electrochemical processes within a battery. The data collected from EIS is typically visualized using Nyquist and Bode plots, revealing resistive and capacitive characteristics of the system. Common models include:

Randles Circuit: Represents charge transfer and diffusion mechanisms.
Transmission Line Models: Suitable for porous electrode materials.
Fractional Order Models: Used for complex impedance behaviors.

Energsoft is a leading software-as-a-service (SaaS) platform that enhances battery analysis by leveraging artificial intelligence (AI) and cloud computing. By integrating EIS data, Energsoft provides:

Automated Impedance Analysis: AI-driven algorithms simplify the interpretation of EIS spectra.
Predictive Maintenance: Early fault detection based on impedance trends.
Real-Time Monitoring: Cloud-based dashboards for remote battery diagnostics.
Data Correlation with Performance Metrics: Linking EIS insights with charge cycles, temperature variations, and operational conditions.

Find Out More

EIS is widely employed in battery development and quality assurance. It enables researchers and engineers to:

Identify degradation mechanisms within a battery.
Optimize material compositions for improved efficiency.
Evaluate State of Health (SoH) and State of Charge (SoC).
Diagnose performance inconsistencies and manufacturing defects.

Why we use nonlinear problems? EIS model is highly nonlinear

Custom Software Development

Our team of expert developers can create bespoke software solutions tailored to the unique needs of your business. From concept to deployment, we work with you every step of the way to ensure your software meets your battery exact requirements.

Here is a small example of the following Rendles and Nelder-Mead techniques:

The program models an electrochemical system (battery) using a Randles Circuit.
It calculates impedance based on resistors and capacitance.
It compares computed impedance to real-world measurements and adjusts the parameters.
It finds the best values of R1, R2, and C using optimization.

This is useful for battery diagnostics, quality testing, and predicting battery lifespan.

Fitted Parameters: R1 = 9.8, R2 = 105.3, C = 9.5e-07
This helps researchers and engineers better understand battery behavior and optimize performance! 🚀

Examples of the different techniques we use include Randles

def randles_circuit(frequencies, R_s, R_ct, C_dl):

"""Simulates impedance response of a Randles circuit model."""

omega = 2 * np.pi * frequencies

Z_cdl = 1 / (1j * omega * C_dl) # Capacitance impedance

Z = R_s + (R_ct * Z_cdl) / (R_ct + Z_cdl) # Randles model

return Z

def fit_eis_data(frequencies, impedance):

"""Fits the Randles circuit model to given EIS data."""

def objective(params):

R_s, R_ct, C_dl = params

modeled_impedance = randles_circuit(frequencies, R_s, R_ct, C_dl)

return np.concatenate([(modeled_impedance.real - impedance.real),

(modeled_impedance.imag - impedance.imag)])

initial_guess = [5, 50, 1e-6]

fitted_params, _ = opt.leastsq(objective, initial_guess)

return fitted_params

Optimization techniques with Nelder-Mead

public static void FitModel(double[] frequencies, Complex[] measuredImpedance)

{

// Initial guesses for parameters [R1, R2, C]

double[] initialGuess = { 10.0, 100.0, 1e-6 };

var objective = ObjectiveFunction.Value(x => CostFunction(x, frequencies, measuredImpedance));

var optimizer = new NelderMeadSimplex(1e-6, 1000);

var result = optimizer.FindMinimum(objective, initialGuess);

// Fitted parameters

double R1_fitted = result.MinimizingPoint[0];

double R2_fitted = result.MinimizingPoint[1];

double C_fitted = result.MinimizingPoint[2];

// Display results

Console.WriteLine($"Fitted Parameters: R1 = {R1_fitted}, R2 = {R2_fitted}, C = {C_fitted}");

}

Transform Your Business with Energsoft - Predictive Battery Analytics Software's Software Solutions

Are you looking for innovative software solutions that can help take your business to the next level? Look no further than Energsoft - Predictive Battery Analytics Software. Our team of experts has 100+ years of experience creating customized software products that are tailored to your specific needs in modeling, machine learning and battery science. From web applications to ETL development, AI pipelines or R&D we have the expertise to help your business succeed.

Schedule a consultation and demo

Predictive Battery Analytics Software

If you’re looking to enhance the modeling capabilities

Create a Cost Function for Fitting

Integrate Optimization Algorithms

Cloud Solutions

Electrochemical Impedance Spectroscopy

24/7 Support

Welcome to Energsoft - EIS Modeling Software

Electrochemical Impedance Spectroscopy

Electrochemical Impedance Spectroscopy

Electrochemical Impedance Spectroscopy

Fitting EIS curve

Electrochemical Impedance Spectroscopy

Electrochemical Impedance Spectroscopy

Modelling EIS

Electrochemical Impedance Spectroscopy

Cloud Computing and EIS

Cloud Computing and EIS

Cloud Computing and EIS

Cloud Computing and EIS

Testing and QA with EIS

Cloud Computing and EIS

Testing and QA with EIS

Monitoring Batteries

Cloud Computing and EIS

Testing and QA with EIS

Fitting and EIS Models

EIS Modeling: Understanding Battery Impedance

Find Out More

Why we use nonlinear problems? EIS model is highly nonlinear

Custom Software Development

Examples of the different techniques we use include Randles

Optimization techniques with Nelder-Mead

Transform Your Business with Energsoft - Predictive Battery Analytics Software's Software Solutions

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