Career Opportunities with this Course
The curriculum is tailored to kickstart your career as
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Powertrain Simulation EngineerPowertrain Testing & Validation Engineer
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Powertrain Testing & Validation Engineer
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Component Testing & Validation Engineer
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Electric Vehicle & Component Benchmarking Engineer
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Testing and Performance Evaluation Engineer
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Vehicle Integration Engineer
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Cell Testing & Battery Pack Testing Engineer
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Homologation & Certification Engineer and more
Detailed Course Syllabus
Electric Vehicle Technology Certification Course
Module 1
Module 1 of the master course provides comprehensive coverage of various topics, including "Well to Wheel and Pump to Wheel analysis" for EVs with ICE vehicles, EV subsystems and architecture, different cell chemistries and their behavior, types of cells used for tractive applications, characteristics and working principles of different types of motors, case studies of existing traction electric motors, the motor selection process for vehicles, an overview of Battery Management Systems (BMS) and motor controllers, regenerative braking, EV auxiliary components such as HVAC systems and cooling/heating systems, EV charging systems and infrastructure, powertrain calculations and component sizing, exposure to vehicle thermal management components, integration of high voltage systems in different vehicles, and an overview of simulation tools at cell, pack, and subsystem levels. By the end of Module 1, learners will gain a comprehensive understanding of EV architecture and functioning.
MATLAB Scripting for 1-D Simulation
Module 2
Module 2 of the master course delves into various topics, including the foundation of MATLAB GUI, data types, script creation and editing, basic math operations, importing and exporting data into MATLAB, graphical plot creation including 2D and 3D plots, bar plots, and histograms, matrix and array operations encompassing functions and math operations, and basic MATLAB programming involving loops and conditional statements. By the end of Module 2, learners will gain proficiency in utilizing the MATLAB software.
MATLAB - Simulink for System Modeling
Module 3
Module 3 of the master course focuses on various topics, including the foundation of MATLAB-Simulink GUI, exploring Simulink library and features, practising commonly used Simulink blocks, understanding Simulink operations, modelling programming constructs, working with continuous and discrete systems, selecting solvers, grasping workspace and model protection concepts, creating model masks and libraries, and practical applications of MATLAB-Simulink such as vehicle aerodynamic force modelling, thermal modelling of a house, and Nickel Metal Hydride Battery modelling. By the end of Module 3, learners will be able to effectively utilise the Simulink software for various applications.
EV Powertrain - Quasi Static Modeling
Module 4
In Module 4 of the master course, learners delve into various topics, including understanding the EV powertrain system and its dynamic behavior, exploring parameters that influence performance, studying driving cycles and their significance (such as NEDC, Artemis Rural/Urban/Highway, FTP-75, WLTP, RDC, acceleration and gradient test cases), comparing drive cycles, generating real-time drive cycles with test vehicles, modelling resistive forces that affect vehicle performance (rolling resistance, grade resistance, aerodynamic resistance, acceleration, and inertial forces), and analyzing the impact of each force on performance. Module 4 also includes tasks like creating traction battery models, performing hand calculations for pack parameter estimations, understanding cell datasheets, and modelling packs to evaluate battery power, current, operational C-rates, energy consumption per kilometer, total energy consumption for drive cycles or required range, and configuring cell connections in series and parallel. Additionally, learners undertake vehicle projects involving the Ather 450X, Nissan Leaf, and Student Formula vehicles. By the end of Module 4, learners will gain the ability to analyze the effects of each parameter, make analytical decisions based on simulation results, and select components such as transmission gear ratios, electric motors (torque, RPM, power), battery packs (capacity, current, C-rate, energy per kilometer), conductors (wires, busbars), and contractors/fuses (maximum current).
EV Powertrain - Dynamic Modeling
Module 5
Module 5 of the master course encompasses several vital topics, including the comparison metrics of powertrain approaches, modelling vehicle resistive forces and their impact on performance, studying torque demands and limitations, analyzing different conditions within the available power, introducing controller functions such as traction force estimation and designing control systems, formulating driver models, exploring PID controllers and their tuning methodologies, adhering to driver model standards, and dynamic subsystem modelling involving traction motor, transmission system, and traction battery. By completing Module 5, learners will gain the ability to estimate various parameters, including vehicle performance metrics like acceleration (e.g., 0 to 60 km/h, 0 to 100 km/h), vehicle gradeability, power estimation based on torque and speed demands, estimation of torque and speed demands for different power availability, battery current and C-rate estimations, battery power and energy estimations, and battery losses estimations. Furthermore, the module includes vehicle projects focused on the Ather 450X, Nissan Leaf, and Student Formula. By the end of Module 5, learners will have the competence to verify and select appropriate motors and batteries for specific electric vehicles, ensuring they perform according to the desired requirements.
EV Subsystems Hands-On Training
Module 6
Module 6 of the master course provides learners with a comprehensive understanding of various aspects, including the practical working of basic electric vehicle components, visualizing and comprehending their functionality, such as motors, motor controllers, batteries, BMS, cell technology, throttle, charger, and EV wiring (LV and HV). Learners also gain knowledge of cell fundamentals, enabling them to select cells for specific applications through testing and analyzing their characteristics under different scenarios. An overview of the Battery Management System (BMS) hardware and software interface is covered, allowing learners to modify protection parameters and explore different functionalities using test cases. Hands-on exposure to battery pack assembly methods, components, and equipment in battery pack building is provided. Additionally, learners learn about motor controller functions and how to optimize parameters based on application requirements. The module also offers practical exposure to vehicle testing, including the role of a vehicle testing engineer, industry-level pre-vehicle testing protocols and ARAI standards, the importance of electric vehicle testing and validation, equipment used for vehicle testing, data acquisition tools, drive cycle development for various scenarios (urban, suburban, highway, gradeability, acceleration), standard vehicle testing procedures, driver safety considerations, maintaining a vehicle test tracker, methods for data sorting and analysis, and preparation of vehicle test reports. By the end of Module 6, learners will have acquired practical knowledge of electric vehicles, understanding their basic components and functionalities, as well as a solid foundation in EV testing.
Advanced Traction Motor & Regenerative Energy Modeling
Module 7
Module 7 of the master course delves into several important topics, including motor operating characteristics and modes (braking and motoring), studying the steady-state operating region of electric motors, comprehending field weakening of motors, estimating motor performance from datasheets, conducting numerical calculations to determine stall torque, nominal torque, peak torque, nominal speed, and a peak speed of a motor. The module primarily focuses on advanced motor modelling, analyzing motor current in relation to torque and motor voltage in relation to RPM, and utilizing simulation data to guide motor selection. Learners also explore the working of regenerative braking in electric vehicles, studying motors operating in regenerative mode and the limitations of regenerative capabilities in cells and battery packs. Additionally, friction and regenerative braking fractions are modelled, and a motor model incorporating regenerative limitations is developed. Estimation of regenerative power in the motor during regenerative mode using regen control logic is covered. By the end of Module 7, learners will acquire deeper skills and understanding of traction motors, enabling them to optimize motor models with maximum accuracy. They will gain knowledge of cell selection based on simulation data, be able to plot motor regenerative power, current, voltage, and torque, analyze motor operating points in regenerative mode, and estimate the vehicle's range with and without regeneration.
Advanced Transmission Modeling & Auto Gear Optimisation
Module 8
Module 08 of the master course provides a comprehensive study on the detailed modelling of transmission systems applicable in electric vehicles (EVs). Learners will understand the principles and necessity of single-speed and multi-speed transmissions, including the equivalent mass variation of the vehicle with respect to gear ratio and its performance diagram. Numerical hand calculations will be performed for gear ratio sizing in both single-speed and multi-speed transmissions, considering factors such as motor speed, vehicle maximum speed, gradeability, performance requirements, motor operating regions, and the impact of gear ratio on battery energy consumption and motor efficiency. An optimization study will be conducted to determine the best gear ratio for optimal performance and efficiency. The module also includes a case study on the design of a two-speed transmission, involving numerical hand calculations for the transmission model and studying the optimization effect of gear ratio on battery energy consumption and motor efficiency. Learners will gain proficiency in programming linear search algorithms using advanced MATLAB scripting, such as for loops, to identify the optimum gear ratio for the two-speed transmission. The analysis of motor operating points for the first and second gear in the case of a two-speed transmission will also be covered. By the end of Module 08, learners will be exposed to the process of sizing an efficient and high-performing transmission system for electric vehicles, equipping them with the knowledge to make informed decisions regarding transmission system design.
Electric Vehicle Testing & MCU Tuning
Module 9
Module 09 of the master course imparts knowledge and skills related to practical on-road electric vehicle testing, practical inertial dynamometer electric vehicle testing for MCU tuning, and practical cell testing. In the on-road testing scenario, learners will conduct tasks such as measuring actual vehicle dimensions, test case and route planning, data collection from various test cases, data sorting and storage methods, importing test data into MATLAB and Simulink models, validating simulation models using real-time data, and optimizing the simulation model and electric powertrain parameters. During the inertial dynamometer testing for MCU tuning, the testing vehicle will be loaded onto the dynamometer, and tasks including test case planning, data collection from the dynamometer, MCU, and BMS, observation of the effect on vehicle performance, throttle response, and current consumption profile, defining tuning parameters, visualization and data analysis, comparison, and documentation will be carried out. The module also covers practical cell testing, providing learners with a detailed understanding of cell and battery testing, test standards and methods, data collection, visualization, and analysis. Learners will gain insights into how cells are tested, perform basic cell tests using specialized equipment, analyze the results, interpret cell behaviour in real time, and document the cell test results. The module also emphasizes the selection of cells for various applications. By the end of Module 09, learners will have practical experience and proficiency in conducting on-road electric vehicle testing, inertial dynamometer testing for MCU tuning and cell testing. These skills will enable them to gather and analyze real-world data, validate simulation models, optimize electric powertrain parameters, and make informed decisions in selecting and testing cells for different applications.
Validation of Simulation with Real-Time Vehicle Testing
Module 10
Module 10 of the master course is dedicated to validating the simulation model and optimizing the electric powertrain parameters. Learners will utilize real-time data acquired from the EV's data acquisition system and input it into their simulation models to validate the results obtained from quasi-static and dynamic modelling. By comparing the actual test cases with the simulation results, learners can assess the accuracy of the model and explore methods to enhance its precision. The module also covers the study of energy consumption in both simulation and actual testing, identifying differences between the two and fine-tuning the model to minimize discrepancies. Learners will define the limitations of the model and learn techniques to extend its boundaries. Ultimately, they will prepare a comprehensive model validation report. Upon completion of module 10, learners will possess the skills to validate simulation models, optimize them for increased accuracy, and achieve maximum precision in their electric powertrain analysis.
Tesla Thermal Management (Heat Pump) & High Voltage Systems
Module 11
Module 11 of the master course provides learners with a comprehensive understanding and exposure to heat pump and non-heat pump-based thermal management systems. They will explore the applications of these systems in cooling and heating various components such as the cabin, battery, motor, and power electronics. The module also highlights the energy-saving benefits of heat pump-based systems and delves into the high-voltage components present in modern Tesla vehicles, including the charging unit, power distribution, HV wiring connections, DC-DC converter, and safety components. Learners will gain insights into the functionalities, working principles, advancements, and innovations of thermal and power electronic components. Furthermore, a comparison between the thermal and power electronic components of Chevy Bolt and Nissan Leaf will be conducted, focusing on system architecture, components, simplicity or complexity, number of parts, and optimization. By the end of module 11, learners will have a detailed understanding of thermal management systems, the importance of energy savings, and the HV-LV system and safety components found in electric vehicles.
Advanced Battery Cooling/Heating & Motor Cooling
Module 12
Module 12 of the master course provides learners with a comprehensive understanding of the motor cooling system and battery cooling system in electric vehicles (EVs). Learners will explore various types of losses in an electric motor, including copper losses, hysteresis losses, iron and eddy current losses, switching losses, and friction and windage losses. The module also covers different motor cooling strategies such as active cooling and passive cooling, along with sizing, modelling, and analysis of electric motor coolant flow rate. Additionally, learners will study the losses in a battery pack due to internal resistance, interconnections resistance, and bus bar connections. They will also delve into modelling and analyzing the battery cooling system, exploring different cooling strategies like active cooling and passive cooling. Estimation of battery energy consumption for different cooling methods and analysis of battery temperature variation will also be covered. By the end of module 12, learners will have gained in-depth knowledge of the thermal management of the traction motor and battery system in EVs.
Advanced HVAC System Modeling & Energy Consumption
Module 13
Module 13 of the master course provides learners with an understanding of the Heating Ventilation and Air Conditioning (HVAC) system in electric vehicles (EVs). Learners will explore the various loads acting on the HVAC system, including metabolic loads, ambient loads, ventilation loads, and radiation loads. They will study the parameters influencing these loads, such as weight and height, and examine the variation of metabolic load based on passenger and driver activities. The module covers the types of radiation loads and explains the direct and reflected radiation loads on the HVAC system based on factors like transmissivity, surface area, angle of incidence of the sun's rays, ground reflectivity, and vehicle body transmissivity. Learners will also understand the ambient load on the cabin due to factors like ambient temperature, car surface area, and vehicle velocity variation. The module delves into the ventilation aspect of the HVAC system, considering the mass flow rate of air and ambient temperature. Power loss calculations due to ventilation mass flow rate, air pressure, and temperature are discussed. Learners will estimate cooling and heating loads as well as the energy consumption of the battery by the HVAC system. Additionally, the module covers the sizing of HVAC system components such as the heater, cooler, and radiator. By the end of module 13, learners will have the knowledge and skills to correctly size the HVAC system for an electric vehicle.
Extended Vehicle Testing & Validation
Module 15
Module 15, the final module of the master course program, involves an extended offline visit to address any missed tasks from the previous offline visits. It provides an opportunity to clarify doubts and seek clarifications regarding offline visits. Additionally, learners are required to submit all the necessary documentation and reports. This module marks the conclusion of the master course program.
Course Fee
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Master Course in Electric Vehicle Powertrain Design & Validation.
The course fee is ₹1,20,000 + ₹21,600 (18% GST) = ₹1,41,600 (Paid in 12 EMI's) (Without Placement Assistance)
12 x ₹11,800.00
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