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PyBaMM User - Physics-Informed Battery Modelling

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Training Module & Schedule
DAY - 1 DAY - 2 DAY - 3 DAY - 4 DAY - 5 DAY - 6 DAY - 7 DAY - 8
Introduction to Cell Datasheet Core Electrical Parameter
Key Topics
  1. Nominal Capacity
  2. Voltage Limits
  3. C-Rate
  4. Internal Resistance
  5. Tolerance
  6. PyBaMM Mappings
Main Activities
  1. Datasheet walkthrough + python coding
    • Dictionary
    • Functions
    • LF280K_Cell Class
Documents to Read / Explore:
  1. EVE LF280K Datasheet (Electrical section)
  2. PyBaMM Chen2020 Parameter Set
  3. Battery University – How to Read a Datasheet
Expected Outcome:
  1. Able to extract parameters from LF280K datasheet and prepare Python inputs for simulations
 1.5 Hours
Standard Charge/Discharge Curves & C-Rate Behavior
Key Topics:
  1. Datasheet curves
  2. IR drop
  3. C-rate effects
  4. SPM simulation
Main Activities:
  1. Plot curves + First PyBaMM SPM run + Validation (±5%)
Documents to Read / Explore:
  1. EVE LF280K Charge/Discharge Curves
  2. PyBaMM SPM Examples
  3. Battery University – Discharge Characteristics
Expected Outcome:
  1. Can plot & validate curves using PyBaMM SPM
 1.5 Hours
Temperature Operating Range & Thermal Effects
Key Topics:
  1. Temp limits
  2. Capacity/Power fade
  3. Corrections
Main Activities:
  1. Temp effect analysis + PyBaMM temperature sweep
Documents to Read / Explore:
  1. EVE LF280K Thermal Section
  2. PyBaMM Thermal Models
  3. Battery University – Temperature Effects
Expected Outcome:
  1. Can apply temperature corrections in simulations
 1.5 Hours
Battery Chemistries (LFP, NMC, NCA, LTO)
Key Topics:
  1. Chemistry comparison
  2. LF280K as LFP
  3. Parameter sets
Main Activities:
  1. Chemistry deep-dive + OCV plotting
Documents to Read / Explore:
  1. EVE LF280K Datasheet
  2. PyBaMM Parameter Sets (Chen2020, Marquis2019)
  3. Battery University – Lithium Chemistries
Expected Outcome:
  1. Can select correct chemistry & PyBaMM parameter set
 1.5 Hours
Pack Configuration (Series & Parallel)
Key Topics:
  1. S/P calculations
  2. Scaling
  3. Balancing
Main Activities:
  1. Pack design + Extend LF280K_Cell class
Documents to Read / Explore:
  1. Battery University – Series/Parallel
  2. PyBaMM Pack Examples
  3. Pack Design Guidelines
Expected Outcome:
  1. Can design and calculate any S/P pack configuration
 1.5 Hours
Application Description & Basic Use-Case
Key Topics:
  1. e-rickshaw
  2. Solar
  3. 2W profiles
  4. DoD
  5. Cycle count
Main Activities:
  1. Use-case mapping + Throughput calculation
Documents to Read / Explore:
  1. EVE Application Notes
  2. India EV Use-Case Profiles
  3. Battery University – DoD & Lifes
Expected Outcome:
  1. Can define use-case parameters for simulations
 1.5 Hours
Simulations (Cycle Life, SOC & Calendar Aging)
Key Topics:
  1. Full workflow
  2. SPM → DFN
  3. Aging models
Main Activities:
  1. End-to-end PyBaMM simulation + Report generation
Documents to Read / Explore:
  1. EVE Cycle & Calendar Data
  2. PyBaMM Aging Examples
  3. Course Template Notebook
Expected Outcome:
  1. Can run complete simulations and generate professional reports
 1.5 Hours
Doubt Clearing + Next Level Intro
Key Topics:
  1. Q&A + Stage 2 Roadmap
Main Activities:
  1. Open discussion + Preview
Documents to Read / Explore:
  1. All prior documents
  2. Stage 2 Preview Slides
  3. BMS & Safety Standards
Expected Outcome:
  1. Fully prepared for Stage 2 (BMS, Thermal, Advanced Modeling)
 1.5 Hours
Limited Enrollment Active

Profession Battery Simulation Training

Join the industry's most comprehensive certification program. Gain hands-on experience with real-world battery modeling and simulation.

Complete Program Fee
₹2,000

Inclusive of GST fees.

Invoice will be raised by RAMSOL PVT LTD-(Parent Company GST No: 33AACCR7379G1Z6)

Register Now
Only Limited Slots Available!

Eligibility

  • Basic understanding of Physics and Chemistry (Battery basics).
  • Familiarity with Python programming (variables, loops, and libraries).
  • Interest in learning Physics-Informed Battery Modeling using PyBaMM.
  • Exposure to numerical simulation tools is a plus.

Training Objectives

  • Introduce participants to PyBaMM architecture and simulation flow.
  • Develop proficiency in model development and parameter estimation.
  • Enable participants to simulate battery degradation and capacity fade.
  • Familiarize learners with thermal modeling and multi-model comparison (SPM vs DFN).
  • Build capability to export results and automate battery analysis tasks.

Computational Requirements

Standard Laptop/PC with minimum 8GB RAM

Software Tools

Python 3.x, Jupyter Notebook, PyBaMM Library

Ecosystem & Hiring Companies

Explore the Industrial Landscape

Tesla
BYD
NIO
Rivian
Lucid Motors
VinFast
XPeng
Hyundai Motor Company
Volkswagen Group
General Motors

Tata Motors
Mahindra Electric
Ola Electric
Ather Energy
TVS Motor Company
Bajaj Auto
Hero MotoCorp

Simple Energy
Euler Motors
Ultraviolette Automotive
Tork Motors
Revolt Motors
Pravaig
Emflux Motors
Matter Motor Works
Bounce Infinity
River Mobility

Okinawa Autotech
Pure EV
BGauss
ESprinto
Altigreen
Omega Seiki Mobility
Keto Motors
Ampere Vehicles
Strom Motors

Exide Industries
Amara Raja Energy & Mobility
Log9 Materials
Sun Mobility
Exponent Energy
ChargeZone
Bosch India
Continental Automotive
Sona Comstar
Tata Agratas
Statiq
Delta Electronics

Yulu
Zypp Electric
BluSmart
EVeEZ
Bounce Infinity (Fleet)

We have partnered with interview partners from the Battery, EV, Energy Storage Sectors, Renewable Energy, Battery Management Systems, Simulation and Engineering, and Analytics.

Interview opportunities will be offered to participants who demonstrate readiness through a completed GitHub repository and a qualifying AI assessment score.

See Our Training in Action

Watch these highlights to see how we cover each core topic in our intensive sessions.

Introduction
Exercise-1
Exercise-2
Exercise-3
Exercise-4

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