Master Course Highlights

  • Course Duration

    36 weeks (Blended)

  • Project Based Learning

    Build, Implement, Test & Calibrate BMS algorithms for SOC, SOH & Cell Balancing

Master Course Overview

  • Foundation to Cell technology & 1-D simulation

  • Hand-on with Li-ion cell testing, characterisation & parameter extraction

  • Develop EQC based cell 1-D models for behaviour prediction (Rint, 1RC & 2RC)

  • Learn Model Management, Model Standards & Simulation based testing

  • Learn SIL, PIL, Embedded C, Code generation & Real time implementation

  • Model based Pack Design & Cell Balancing algorithms development

  • Introduction to State Estimations & Filters

  • Kalman filter based SOC Estimation

  • Least Square and Impedance based SOC Estimation

Career Opportunities with this Course

  • BMS development algorithm engineer (R&D)

  • BMS testing, validation & calibration engineer

  • Cell & pack testing engineer

  • BMS application engineer

  • BMS Virtual validation & Software test engineer

  • Cell and Battery Characterization engineer

Detailed Course Syllabus

Li-Ion Cell Chemistry & Technology

Module 1

The 1st half of Module 1 of the Master the course covers the fundamentals of electrochemical cells, cell constructions, types of cell formats, cell materials, cell chemistries, electrochemical reactions in cells, cell terminologies, cell failure modes and safety devices are discussed. Some fundamental calculations on parameters such as cell potential, capacity and energy are also discussed by referring to the reduction potential chart. And the 2nd half of Module 1 describes lithium-ion cells in more detail. Various types of Li-ion chemistries are discussed along with their properties and characteristics. The fundamentals of electrochemistry such as Fick’s law of diffusion and Peeukert’s law are discussed briefly. By the end of the module, the the learner will be able to get a good grasp of crucial electrochemical cell properties, behavior, and characteristics.

MATLAB Scripting for 1-D Simulation

Module 2

Module 2 of the master course will cover the topics such as foundation to Matlab programming from basics to Advance level. Module 2 will cover a massive amount of tool skills such as basic math & matrix application, import & export data, plot & visualization of data, basic programming concepts(if-else, loops), functions, logic development, relational operation, etc. module 2 also covers hands-on training with software & provides a foundation for career opportunities to start as a Matlab developer. By the end of Module 2, the the learner will be able to use Matlab software with fluency.

MATLAB Simulink for System Modeling

Module 3

Module 3 of the master course will cover the topics such as the foundation of the concepts of Simulink. It involves how to make use of blocks to construct an algorithm or equation, how to set up the programming constructs, logic, basic math, etc. Further data visualization, importing, exporting & analyzing. It is a platform to design, develop, test & validate the system. In module 3 we also cover hands-on training with software & this training will aid learners to explore career opportunities as Model-Based System Engineers (MBSE). By the end of module 3, the learner will be able to use Simulink software along with several applications with ease.

Equivalent Circuit Based Li-Ion Cell Modeling

Module 4

In module 4, the learner uses the knowledge acquired in modules 2 and 3 to create a basic mathematical model of a Li-ion cell in Matlab and Simulink using principles of Thevenin’s equivalent circuit. Starting off with a very basic model called RINT, The learner first understands the method of cell modeling (data-driven model) and then progresses to an the advanced model called 1 RC model. The model is then simulated for different current loads such as constant current and pulse discharge. At the end of the module 4, the learner will be able to understand how Li-ion cells are modeled and simulated based on Thevenin's principles.

Li-Ion Cell Testing and Characterisation

Module 5 - Lab Visit

Module 5 of the master course covers the fundamentals of Cell Testing. This module is conducted offline. The different standards of cell testing such as IEC/ISO/UL/FreedomCAR and the different categories of testing such as static test, pulse test, thermal test, and life cycle test are discussed. The learner then gets hands-on experience with the cell testing hardware (Neware BTS) and the thermal chamber and performs the basic cell testing activities. The learner will also use tools such as Excel and Matlab to perform some simple 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: Understand how Li-Ion cells are tested, Understand different procedures for cell testing, Analyze the test results and interpret the cell behavior in real-time & Create a simple program for extracting cell parameters

1 RC Lithium Ion Cell Model Validation

Module 6

In Module 6 of the master course, The data obtained during the live session of the module 5 is utilized in the 1RC cell model created in module 4. Using the data obtained and modeling techniques from module 4, the learner performs an important step in modeling called Validation. Validation of the model is done to check and verify the model’s behavior to different inputs and to analyze how close the model’s behavior is to real life. By the end of module 6, the the learner will be able to understand the method of Model Validation and Analyze the drawbacks of the model.

2 RC Lithium Ion Cell Model Validation

Module 7

Module 7 of the master course is a project-based module. Using all the knowledge acquired since module 1, The the learner has to create a 2RC cell model using Matlab and Simulink and validate the model for different inputs. The results from the 1RC model (from module 6) and the 2RC model is compared and the difference between the model performance is analyzed. By the end of module 7, the learner has a good grasp of cell modeling techniques and model validation.

Stateflow for Logic Driven System Modeling

Module 8

Module 8 of the master course will cover the topics such as the foundation of the concepts of Stateflow, how to set up time-based events, task-based events, trigger-based events, condition-based events, debugging tables & charts, design of logic & control part of algorithms. Module 8 will also cover hands-on training with Stateflow applications with examples. By the end of Module 8, the learner will be able to use Stateflow applications in system modeling with ease.

Model Management & MBD Standards

Module 9

Module 9 of the master course will cover the topics such as the foundation of the Automotive software development process (V-type model & MBSE model), creating design & test requirements & setting up them in Simulink, the system architecture development, Model & data management, concepts of MBSE project management, data type creation & setup, the concept of report generation of the project, Source control, the concept model an advisor with compliance to standards & performance. Module 9 will also cover hands-on training with tools such as Simulink requirements & many others and provides an overview of the system engineering. By the end of Module 9, the the learner will be able to conceptualize how to manage & maintain the project of the MBSE application.

Battery Management System Algorithm Modeling (Single Cell)

Module 10

Module 10 of the master course will cover topics related to Battery Management Systems (BMS) Algorithms & protection functionality developments. First will start with an understanding the basics of BMS applications, the need for BMS modeling & simulation, Process of model development in the Simulink environment & will also learn BMS protection functionalities such as overvoltage, Undervoltage, overcurrent, etc & estimations of cell parameters such as SOC by coulomb & voltage-based approach. By the end of Module 10, the learner will be able to understand the system modeling of BMS, functionalities & basic estimation methods.

Simulation Based Model Testing

Module 11

Module 11 of the master course will cover topics related to system or algorithm testing. It involves test requirements setup to model, setting up test cases & scenarios for testing, creating test harness for unit testing, setting up a model with different testing methods (Internal, external & Logic), analyzing the results with runtime analysis methods & creating test suites for the unit to system level testing such as simulation test, baseline test & equivalence test. Module 11 will also cover hands-on training with the Simulink test & provide career opportunities in software testing in MBSE. By the end of Module 11, the learner will be able to use the Simulink test tool for testing several applications.

Model Design Verification

Module 12

Module 12 of the master course will cover the topics related to the verification of a designed system or model, System design verification is pre-work that needs to be done before moving to the code generation part. In this module, we will learn several concepts which deal with identifying errors in models, algorithm coverage, property proving concepts, automatic test generation, etc with which we can make sure that system or model is ready for code generation. During the tenure of module 12 learners will get hands-on experience with the design verifier tool which is part of Simulink. By the end of Module 12, the learner will be able to use the design verifier tool for making the model ready for code generation.

Code Generation - Single Cell BMS - MIL, SIL, PIL & Hardware

Module 13

Module 13 of the master course will cover the topics such as hands-on hardware with practical implementing & working on Model in a loop (MIL), Software in a loop(SIL), Processor in the loop & actual hardware in Loop, With a deep understanding of plant & controller model integration, SIL testing & simulation, PIL verification & Several approaches for code generation. Understand code generation requirements, setup procedure, methods of code generation (Simulink coder, embedded coder), monitor & tune concepts, final deployment & testing. In this module single-cell BMS is the target hardware from an application point of view. By the end of Module 13, the learner will be able to use the Code generation tool with ease for BMS Algorithms.

Cell Balancing Theory and Modeling

Module 14

Module 14 of the master course covers the theory of cell balancing. Topics such as the causes of imbalanced cells, the requirement of cell balancing, balancing approaches, and algorithms are discussed in theory. After completing the theoretical aspects of cell balancing, the cell balancing modeling aspects are introduced. The algorithm for cell balancing is discussed with the help of a flow chart, which shows the conditions and actions necessary at each stage of cell balancing. Tools such as Simulink and Stateflow are used to create, test, and simulate a basic 3-cell cell balancing model. At the end of module 14, the learner will be able to understand the basics of cell balancing and is able to implement, test, and simulate a basic cell balancing algorithm for a 3-cell model.

Advanced Battery Protection Feature Theory and Modeling

Module 15

In Module 15, the learner applies the knowledge acquired in Modules 2 and 3 to create basic and advanced battery protection features. The learner will understand key battery parameters such as battery/cell voltage, current, and temperature, and how to control them by setting appropriate limits. By the end of Module 15, the learner will be able to comprehend and practice industry-level protection features and modelling.

Foundation to Kalman Filters

Module 16

Module 16 of the master course covers the theory of the Kalman filter & will learn the single-dimension application of the Kalman filter to multi-dimension. In this module, you learn the hands-on calculation of the Kalman filter application & Kalman filter flow. By the end of Module 16, the learner will be able to understand the Kalman filter & its application.

Extended Kalman Filter Based SOC Estimation

Module 17

In module 17 of the master course, The fundamentals of the Kalman Filter learned in module 16 are utilized in designing an an efficient algorithm to estimate the state of charge of a Li-ion cell. The steps involved in the extended Kalman filter such as the state update equation, covariance matrix, prediction equation and Kalman gain are discussed. The learner uses Matlab and Simulink to create and simulate the designed algorithm. By the end of the module 17, the learner has designed and implemented a Kalman Filter algorithm for cell state of charge estimation.

Li-Ion Cell State of Health (SOH)

Module 18

In module 18 of the master course, Another application of the Kalman filter for cell state estimation is explored i.e., the state of health estimation. The fundamentals of cell state of health estimation such as life cycle test, capacity fading, and rise in internal resistance, power fading, and overall cell degradation are explored. After this, an algorithm for the Kalman Filter for the state of health estimation is developed using the concepts learned in module 16. By the end of module 18, the learner had been designed and implemented a Kalman Filter algorithm for cell state of health estimation.

Advanced Algorithm Implementation on NXP Hardware

Module 19 - Lab Visit

Module 19 of the master course will cover topics such as hands-on hardware with practical implementation of cell balancing concepts, Kalman filter-based SOC estimation, impedance tracking-based SOH estimation and advanced protection logic. Final code deployment is carried out for the implementation Algorithm into target hardware(NXP-based controller). In this module, Multicell BMS is the target hardware used from an application point of view. By the end of Module 19, the learner will be able to understand the code generation for Multicell BMS for advanced algorithms & implementation into hardware.

Lab Visit

Lab Visit - 01

Li-Ion Cell Testing and Characterization

During the 1st Lab visit of our master course in Battery Management Algorithm Development, We delve into the fundamentals of Cell Testing, the diverse standards of cell testing, including IEC/ISO/UL/FreedomCAR, and explore various testing categories such as static tests, pulse tests, thermal tests, and life cycle tests. Learners engage in hands-on experiences with cell testing hardware, specifically the Neware BTS, and a thermal chamber. They actively perform essential cell testing activities, utilizing tools like Excel and MATLAB for tasks such as graphical analysis, cell voltage response analysis, capacity estimation, pulse response analysis, internal resistance estimation, and thermal behaviour analysis. By the end of the visit, participants emerge with a profound understanding of how Li-Ion cells are tested, familiarity with different testing procedures, the ability to analyze test results and interpret real-time cell behaviour, and the skill to create a simple program for extracting cell parameters.

Lab Visit - 02

Code Generation - Single Cell BMS - MIL, SIL, PIL & Hardware

In the 2nd Lab visit of our master course in Battery Management Algorithm Development, Learners will delve into hands-on hardware experiences, gaining practical proficiency in Model in a Loop (MIL), Software in a Loop (SIL), Processor in the Loop (PIL), and actual hardware in Loop. The session focuses on a comprehensive understanding of plant and controller model integration, SIL testing and simulation, PIL verification, and various approaches for code generation. Learners will explore code generation requirements, setup procedures, methods such as Simulink Coder and Embedded Coder, as well as concepts of monitoring and tuning. The final deployment and testing will be carried out, with a specific focus on single-cell Battery Management System (BMS) as the target hardware. By the end of this Lab Visit, Learners will seamlessly utilize code generation tools for BMS Algorithms, marking a significant milestone in their mastery of Electric Vehicle (EV) technology.

Lab Visit - 03

Advanced Algorithm Implementation on NXP Hardware

During the 3rd Lab visit of our Battery Management Algorithm Development master course. Learners delve into practical hardware implementation, mastering cell balancing, Kalman filter-based State of Charge (SOC) estimation, impedance tracking-based State of Health (SOH) estimation, and advanced protection logic. The pinnacle of learning is reached as the final code is deployed into NXP-based controllers, specifically the Multicell Battery Management System (BMS). This hands-on experience equips learners with the expertise to comprehend code generation for Multicell BMS, enabling the implementation of advanced algorithms into real-world hardware. By the end of this lab visit, participants emerge with a comprehensive understanding and practical proficiency in advanced battery management algorithms, marking a significant milestone in their mastery of Electric Vehicle (EV) technology.

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Why to Take Master Course from Decibels?

  • Battery Management Algorithm Development course curriculum is laser-focused to prepare you for the development & testing job roles in Industry.

  • You will get to work on real-world projects at our COE to gain practical experience that is equivalent to working in Industry.

  • Our team will handhold you for resume building, interview preparation, communication & documentation skills. And, ensure your job readiness.

Course Pricing Flexibility

  • Master Certification Course in Battery Management Algorithm Development.

    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

    Enroll now

Master Certification Course in Battery Management Algorithm Development

Course Start Date: 28th October 2024

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