Master Certification Course in Battery Materials, Characterization & Digital Twins
Course Duration of 12 Month with Hybrid Mode of Learning
Course Overview
The Master Course in Battery Materials, Characterization & Digital Twins by Decibels Lab offers a comprehensive journey into the core of modern battery technology. Designed for engineers, researchers, and students aiming to specialize in battery R&D, simulation, and testing, the course covers essential topics such as electrochemistry, advanced battery materials, cell formats, and manufacturing processes. Participants will gain hands-on exposure to battery materials, half cell formation & testing, full cell prototyping, cell characterization techniques including CV, EIS, Cyclic Aging, DCIR and more—equipping them with the analytical skills needed to assess and improve battery performance.
In addition to testing and characterization, the course emphasizes simulation and modeling, guiding learners through both time-domain (RC-based) and frequency-domain (Randle circuit) models. It culminates in the development of digital twin frameworks and physics-based models such as Single Particle Models (SPM) and Reduced Order Models (ROM). The course includes hands-on sessions, real lab data analysis, and industry-relevant case studies delivered through recorded lectures and offline lab visits. Learners will gain practical, job-ready skills aligned with the demands of the modern battery and energy storage industry.
This course opens up a wide range of career paths in the growing battery and EV sectors. Graduates can pursue roles such as Battery R&D Engineer, focusing on innovation in materials and cell design; Battery Testing & Validation Engineer, responsible for performance and safety evaluation; and Digital Twin & Simulation Specialist, working on predictive modeling and system optimization. Additionally, opportunities include becoming an EV & Energy Storage Engineer, Battery Manufacturing & Process Engineer, or a Battery Management System (BMS) Engineer, each playing a critical role in the development and deployment of modern battery technologies.
Detailed Course Syllabus
Fundamentals of Electrochemistry & Battery Principles
Module 1
Module 1 provides a foundational understanding of electrochemistry and battery principles essential for battery technology. It covers electrode and cell fundamentals, electrochemical cell types, and key concepts like electrode potential, EMF, and the Nernst equation. The module explores battery structures, types (primary, secondary), and lithium-ion battery chemistry, along with performance metrics such as voltage, capacity, energy density, C-rate, SOC, DOD, SOH, and cycle life. It also delves into electrode/electrolyte interfaces, overpotential, polarization mechanisms, and critical electrochemical laws and kinetics, including Faraday’s Law, Fick’s Law, and the Butler–Volmer and Tafel equations.
Materials and Components of Batteries
Module 2
Module 2 offers a comprehensive overview of battery materials and components, covering various cell formats, active materials (like graphite, LCO, NMC, LFP, etc.), and their crystal structures and redox behaviour. It explores electrolytes, separators, binders, and conductive fillers, along with critical interfaces like SEI and CEI that impact performance and longevity. The module details the battery manufacturing process from electrode fabrication to cell finishing, and introduces advanced battery chemistries such as lithium-sulfur, solid-state, and sodium-ion. It also addresses battery degradation mechanisms and highlights the importance of recycling technologies for sustainability.
Characterization Techniques for Battery Materials & Cells
Module 3
Module 3 offers a comprehensive overview of key characterization techniques used to evaluate battery materials, electrodes, and cells, essential for optimizing performance in energy storage systems. It covers electrochemical methods such as cyclic voltammetry (CV), linear sweep voltammetry (LSV), and Electrochemical Impedance Spectroscopy (EIS), focusing on their principles, experimental setup, and data interpretation. The module also explores material characterization tools including XRD, FESEM and surface area analysis, enabling detailed insights into the structural, morphological, and electrochemical properties of battery components.
Lab Visit: Battery Materials and Cell Prototyping
Module 4
Learners will be exposed to material synthesis to develop anode and cathode materials for different battery chemistries. The visit covers the process of material coating, cell development in a glove box and cell crimping. In addition to these activities, learners will gain exposure to haf cell & coin cell testing.
Direct Current Internal Resistance (DCIR) & Battery Testing
Module 5
This section provides a foundation for understanding DCIR testing, emphasizing its significance in battery analysis and applications. Various DCIR test types are explained, including static capacity tests, peak power tests (CC, CR, CP methods), performance drive cycle tests, and dynamic stress tests (DST), which simulate real-world applications. Life cycle and calendar life tests are discussed to understand aging mechanisms and capacity fade, along with the importance of gathering data for battery simulation models. The module covers the essential setup for DCIR testing, including voltage and current measuring equipment, thermal chambers, and detailed step-by-step configurations. Hands-on applications involve techniques like the current interrupt method for resistance estimation, testing under varying conditions, pulse power characterization, and static capacity evaluation. Key testing standards (Freedom CAR, ISO, IEC) are introduced, alongside standard protocols for extracting OCV curves and integrating cell cycling systems with thermal chambers. The module concludes with an emphasis on data analysis, focusing on OCV curve evaluation and refining resistance-capacitance (RC) parameters.
Lab Visit: Cell DC Characterisation
Module 6
This module covers the depth of Cell Testing & Characterisation from the basics to advance level. Learners will gain practical exposure to conduct the experiments to get the characteristics with OCV, Capacity, Aging and HPPC tests. The learner then gets hands-on experience with the Neware BTS machine and the thermal chamber to perform the testing activities. The learner will also use tools such as Matlab to perform activities such as graphical analysis, cell voltage response analysis, capacity estimation, pulse response analysis, internal resistance estimation, and analyze the thermal behavior of the cell. By the end of the module, the learner is able to analyze the test results and interpret the cell behavior & perform parameter extraction.
Time-Domain Modeling & Parameter Estimation
Module 7
This module explores the mathematical modeling of battery cells, focusing on 1RC and 2RC models. It highlights key model parameters, including ohmic resistance, polarization resistance, and capacitance, while explaining their dependence on SOC, temperature, and aging. The module emphasizes voltage response analysis under various conditions, estimating time constants and identifying voltage regions. Practical aspects include coding for parameter extraction and automated estimation of resistance and capacitance, along with iterative testing and validation of RC models against real-world data.
Electrochemical Impedance Spectroscopy (EIS) & ACIR Analysis
Module 8
This part introduces ACIR (Alternating Current Internal Resistance) and EIS, explaining their principles, significance in cell dynamics, and applications in health and lifetime assessments. It contrasts ACIR and EIS for practical scenarios and explores EIS test types—potentiostatic and galvanostatic—explaining their theories, principles, and applications. Impedance measurement techniques, tools, and frequency ranges for accurate data collection are also highlighted. The module further delves into Nyquist and Bode plot analysis for parameter identification and the preparation of results for simulations, enriching the understanding of impedance analysis in battery systems.
Lab Visit: EIS and ACIR Characterisation
Module 9
In this hands-on lab session, learners gain practical insights into the fundamentals and applications of EIS in battery systems. The session begins with understanding the limitations and board-level applications of EIS equipment. Learners build complex RC circuits on breadboards, simulate responses, and analyze Nyquist and Bode plots using the Hioki impedance analyzer. They extract key parameters (R₀, R₁, C₁, C₂, and Warburg impedance) both manually and via software. The session concludes with EIS testing on prismatic cells at different SOC levels, data interpretation, and a post-assessment quiz to reinforce learning.
Frequency-Domain Modeling & Circuit-Based Analysis
Module 10
The module 10 introduces Randle circuits as an essential component of electrochemical system modeling and their application in battery impedance analysis. It explains components like solution resistance, charge transfer resistance, CPEs, and advanced elements (SEI layer, Warburg impedance). Techniques for parameter identification using Nyquist and Bode plots are emphasized, focusing on the effects of SOC, temperature, and aging. The module covers EIS data application, circuit fitting tools (e.g., Z-view), and the role of software in modeling and data fitting. Validation techniques for Randle circuits are discussed, comparing their accuracy against DCIR-based models.
Electrochemical Modeling & Simulation Techniques
Module 11
Physics-based modeling explores battery systems using principles derived from physical laws rather than empirical data. It highlights the working of electrochemical cells, focusing on electrode reactions, ion transport, and governing equations such as the Nernst equation and Butler-Volmer kinetics. The challenges of such models, like complexity, computational demands, and parameter estimation, are addressed, along with methods to ensure validation and scalability for larger systems. It introduces key modeling techniques, including Single Particle Models (SPM), which simplify battery behavior by analyzing lithium-ion diffusion, and Reduced Order Models (ROM), like the Single Bucket Model, which enable efficient SOC tracking and performance analysis. Practical aspects, such as coding, testing, and tuning models under various conditions, are emphasized. This module equips you with advanced tools to simulate and optimize battery behavior for real-world applications efficiently.
Course Pricing Flexibility
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Master Certification Course in Battery Materials, Characterization & Digital Twins
The course fee is ₹1,30,000 + ₹23,400 (18% GST) = ₹1,53,400 (Paid in 12 EMI's (Without Placement Assistance)
12 x ₹12,783.00
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