EV Energy Simulation Course with MATLAB/Simulink
About our
EV Energy Simulation Course with MATLAB/Simulink
This course offers an immersive experience in the modeling and analysis of electric vehicles. It explores battery, electric motor, and controller systems, using MATLAB/Simulink to simulate energy performance and optimize design. The course covers energy management, propulsion system design, and efficiency analysis of EVs, preparing participants for the development of electric mobility technologies. It focuses on the application of mathematical models for the simulation and design of EVs, including driving simulation and life cycle analysis.
The course provides hands-on experience with simulation tools, enabling students to model and simulate different operating scenarios and analyze the impact of various components on vehicle performance. Students learn to evaluate the energy consumption, range, and performance of EVs. The training prepares students for roles in electric vehicle engineering, propulsion system design, and performance analysis.
EV Energy Simulation Course with MATLAB/Simulink
- Format: Hybrid
- Duration: 3 months
- Hours: 300 H
- Language: English / Spanish
- Registration date: 23-10-2026
- Start date: 12-12-2026
- Available places: 2
799 $
Competencies and results
What you will learn
1. Energy Simulation of Electric Vehicles: MATLAB/Simulink (Complete Course)
- Model electric vehicle components (motors, batteries, inverters) in MATLAB/Simulink.
- Simulate the energy behavior of electric vehicles under different driving conditions.
- Analyze battery performance (SOC, SOH, temperature) and optimize its management.
- Evaluate vehicle energy efficiency and optimize its design to maximize range.
- Design control strategies for electric propulsion systems.
- Use data analysis and visualization tools to interpret simulation results.
- Understand the regulations and standards related to electric vehicles.
- Develop practical skills in simulating electric power systems using MATLAB/Simulink.
- Apply optimization techniques to improve the performance and efficiency of electric vehicles.
- Master the complete simulation process, from model creation to the analysis of results and decision-making.
2. Design and Energy Analysis of Electric Vehicles with MATLAB/Simulink
Here is the requested content:
- Electric Vehicle Systems Modeling: You will learn to create accurate models of electric vehicles using MATLAB/Simulink, including key components such as batteries, electric motors, controllers, and drive systems.
- Energy Consumption Analysis: You will master the tools to simulate and analyze the energy consumption of electric vehicles under different operating conditions, including variations in speed, topography, and driving style.
- Energy Efficiency Optimization: You will explore strategies to optimize the energy efficiency of electric vehicles, such as battery management, energy regeneration, and the design of efficient propulsion systems.
- Electrical Circuit Simulation: You will acquire skills in simulating complex electrical circuits within electric vehicles, including modeling charging systems, inverters, and power converters.
- Electric Circuit Simulation: You will acquire skills in simulating complex electrical circuits within electric vehicles, including modeling charging systems, inverters, and power converters.
- Performance and Range Evaluation: You will learn to evaluate the performance of electric vehicles in terms of acceleration, top speed, and range, and to identify factors that influence these characteristics.
- Battery System Design: You will become familiar with the principles of battery system design for electric vehicles, including cell selection, module configuration, and thermal management.
- Component Integration and Control: You will learn to integrate different components of an electric vehicle into a simulated system and to design control algorithms to optimize its operation.
- Failure Analysis and Safety: You will explore techniques for analyzing potential failures in vehicle electrical systems and for ensuring the safety and reliability of the design.
- Model Implementation and Validation: You will learn to implement electric vehicle models in MATLAB/Simulink and to validate them. The simulation results are compared with experimental data.
- Applications of Artificial Intelligence (AI): Introduction to the use of AI, such as machine learning, to optimize performance, consumption, and energy management in electric vehicles.
3. Comprehensive user-oriented design and validation (from modeling to manufacturing)
You will learn to integrate the entire product development process, from initial model conception to final validation, applying user-centered methodologies. You will develop skills in parametric design, ergonomics, simulation, sustainable materials, 3D visualization, and manufacturing management, ensuring efficient, safe solutions that meet current industry standards.
4. Mastery of Energy Simulation EV: MATLAB/Simulink for Success
4. Mastery of EV Energy Simulation: MATLAB/Simulink for Success
Model and simulate electric vehicle (EV) propulsion systems using MATLAB/Simulink.
Understand the fundamentals of power electronics applied to electric vehicles.
Design and analyze controllers for electric motors and battery management systems (BMS).
Simulate the dynamic behavior of electric vehicles, including acceleration, braking, and energy efficiency.
Optimize the design of key electric powertrain components (motor, inverter, battery) to maximize performance and range.
Analyze the impact of different battery types and charging technologies on vehicle performance.
Apply simulation tools to assess the safety and reliability of EV systems.
Interpret and analyze simulation data to inform decision-making in vehicle design and development. electrics.
5. In-depth Analysis of EV Energy Efficiency: Simulations with MATLAB/Simulink
5. In-Depth Analysis of EV Energy Efficiency: Simulations with MATLAB/Simulink
Modeling and simulation of EV systems using MATLAB/Simulink.
Analysis of energy efficiency in different EV components and subsystems.
Optimization of energy performance by modifying parameters and control strategies.
Evaluation of the influence of external factors (temperature, load) on efficiency.
Design and simulation of battery management systems (BMS).
Analysis of the efficiency of electric motors and their converters.
Simulation of driving scenarios and evaluation of energy consumption.
Implementation of control algorithms to maximize efficiency.
Analysis of results and generation of detailed technical reports.
Validation of models and results by comparing them with data. real.
6. Simulation of Electric Propulsion Systems: Detailed Analysis with MATLAB/Simulink
6. Simulation of Electric Propulsion Systems: Detailed Analysis with MATLAB/Simulink
Modeling and simulation of electric motors, including induction, synchronous, and permanent magnet motors, in MATLAB/Simulink.
Analysis of electrical power conversion systems: rectifiers, inverters, and DC-DC converters.
Simulation of the interaction between the electric motor and the propeller, considering hydrodynamic characteristics.
Design and simulation of control systems for electric propulsion, including vector control and predictive control strategies.
Analysis of the energy efficiency and performance of electric propulsion systems.
Fault simulation and reliability analysis of electric propulsion systems.
Implementation of optimization techniques for the design of electric propulsion systems.
Study of The integration of energy storage systems, such as batteries and supercapacitors.
Analysis of the influence of environmental conditions on the performance of electric propulsion systems.
Use of simulation tools for the evaluation of different configurations of electric propulsion systems in naval environments.
Who this program is for:
EV Energy Simulation Course with MATLAB/Simulink
- Engineers with degrees in Aerospace Engineering, Mechanical Engineering, Industrial Engineering, Automation Engineering, or other similar fields of study.
- Experts and technical personnel working in: Aircraft Manufacturers (OEMs), Maintenance, Repair, and Overhaul (MRO) companies, consulting firms, and technology research centers.
- Specialists in Flight Testing, Aeronautical Certification, Avionics Systems, Control Systems, and Flight Dynamics, who wish to deepen their knowledge.
- Officials and staff of organizations Aeronautical regulators and authorities, as well as professionals involved in urban air mobility (UAM) and eVTOL projects, interested in developing compliance skills.
Recommended requirements: Prior knowledge of aerodynamics, control theory, and strength of materials is recommended. Fluency in English or Spanish at a B2+ or C1 level is essential. We offer supplementary training resources (bridging tracks) to help participants reach the required level.
- Standards-driven curriculum: you will work with CS-27/CS-29, DO-160, DO-178C/DO-254, ARP4754A/ARP4761, ADS-33E-PRF from the first module.
- Accreditable laboratories (EN ISO/IEC 17025) with rotor bench, EMC/Lightning pre-compliance, HIL/SIL, vibrations/acoustics.
- Evidence-oriented TFM: safety case, test plan, compliance dossierand operational limits.
- Mentored by industry: teachers with experience in rotorcraft, tiltrotor, eVTOL/UAM and flight test.
- Flexible modality (hybrid/online), international cohorts and support from SEIUM Career Services.
- Ethics and security: safety-by-design approach, cyber-OT, DIH and compliance as pillars.
Module 1 — Introduction to EV Simulation with MATLAB/Simulink
1.1 Electric Vehicle (EV) Fundamentals and MATLAB/Simulink
1.2 Importance of Simulation in EV Design
1.3 General Structure of an EV Simulation Model in MATLAB/Simulink
1.4 Key Components of an Electric Propulsion System (Batteries, Motors, etc.)
1.5 Introduction to the MATLAB/Simulink User Interface
1.6 Creating a Basic EV Model in Simulink
1.7 Simulating a Simple Driving Cycle
1.8 Analyzing Preliminary Results (Speed, Energy Consumption)
1.9 EV-Specific Tools and Blocks in Simulink
1.10 Introduction to Optimization in EV Simulation
2.2 Battery Modeling for Electric Vehicles: Types and Characteristics
2.2 Electric Motor Modeling: Synchronous, Asynchronous, and Permanent Magnet
2.3 DC-DC Inverter and Converter Modeling: Topologies and Control
2.4 Cooling and Thermal Management System Modeling
2.5 Drivetrain Modeling: Gearboxes and Differentials
2.6 Tire and Rolling Resistance Modeling
2.7 Aerodynamic and Drag Modeling
2.8 Component Integration and Complete System Simulation
2.9 Model Validation: Comparison with Experimental Data
2.20 Parameter Optimization and Sensitivity Analysis
3.3 Introduction to Electric Vehicles (EVs) and Their Importance
3.2 Fundamentals of Energy Simulation in EVs
3.3 Introduction to MATLAB/Simulink for EV Simulation
3.4 Structure and Main Components of an EV
3.5 Course Objectives and Methodology
3.6 Setting Up the Simulation Environment in MATLAB/Simulink
3.7 Review of Essential MATLAB/Simulink Tools and Functions
3.8 Practical Examples of Basic EV Simulation
3.9 Results Analysis and Model Validation
3.30 Introduction to Challenges and Trends in EV Energy Simulation
2.3 Modeling Electric Motors for EVs
2.2 Battery Modeling: Types, Characteristics, and Mathematical Models 2.3 Modeling Motor Controllers (Inverters).
2.4 Modeling the Powertrain and Transmission.
2.5 Modeling Battery Management Systems (BMS).
2.6 Modeling Aerodynamics and Rolling Resistance.
2.7 Integrating Components into a Complete EV Model.
2.8 Analyzing the Energy Consumption of Components.
2.9 Case Studies: Modeling Different Types of EVs.
2.30 Optimization Techniques and Parameter Tuning in Models.
3.3 Design of Electric Propulsion Systems.
3.2 Selection and Sizing of Electric Motors.
3.3 Selection and Sizing of Batteries and Storage Systems.
3.4 Design of the Motor Control System.
3.5 Design of the Energy Management System. 3.6 Thermal Design Considerations
3.7 Charging and Recharging System Design
3.8 Design Efficiency Evaluation
3.9 Case Studies: Design of Different EV Configurations
3.30 Design and Simulation Tools for System Optimization
4.3 Advanced Simulation Techniques in MATLAB/Simulink
4.2 Optimization of Design Parameters using MATLAB
4.3 Monte Carlo Simulation for Sensitivity Analysis
4.4 Scenario and Sensitivity Analysis in EV Simulation
4.5 Introduction to Hardware-in-the-Loop (HIL) Simulation
4.6 Multiobjective Optimization for EV Design
4.7 Design of Advanced Control Strategies
4.8 Implementation of Control Algorithms in Simulink 4.9 Case Studies: Advanced Simulation in Different Applications.
4.30 Analysis of Results and Design Improvement.
5.3 Definition and Measurement of Energy Efficiency in EVs.
5.2 Factors Influencing Energy Efficiency.
5.3 Modeling and Simulation of Energy Consumption in Different Driving Cycles.
5.4 Analysis of the Impact of Mass and Aerodynamics on Efficiency.
5.5 Impact of Temperature on System Performance.
5.6 Analysis of Energy Recovery Efficiency.
5.7 Optimization of Energy Efficiency through Control.
5.8 Analysis of the Efficiency of Different Types of EVs.
5.9 Case Studies: Analysis of Efficiency under Real-World Conditions.
5.30 Conclusions and Strategies for Improving Energy Efficiency.
6.3 Modeling of Induction and Synchronous Motors.
6.2 Modeling of Motor Controllers for Different Motor Types.
6.3 Simulation of Electric Motor Start-up and Stop.
6.4 Simulation of Operation at Different Operating Regimes.
6.5 Simulation of Speed Control Systems.
6.6 Analysis of Propulsion System Efficiency.
6.7 Analysis of Motor and Controller Losses.
6.8 Case Studies: Simulation of Specific Propulsion Systems.
6.9 Design and Optimization of Motor Control Strategies.
6.30 Conclusions and Trends in Electric Propulsion.
7.3 Modeling of Battery Cells: Electrical and Chemical Models.
7.2 Modeling of Battery Packs and Management Systems.
7.3 Battery Thermal System Modeling
7.4 Battery Performance and Degradation Analysis
7.5 Battery Management System (BMS) Strategy Design
7.6 Simulation of the Impact of Charging and Discharging on Battery Lifespan
7.7 BMS Design Optimization
7.8 Case Studies: Simulation of Advanced Battery Systems
7.9 Application of Battery State Estimation Techniques
7.30 Conclusions and Future of Energy Management in EVs
8.3 Introduction to Analysis Tools in MATLAB/Simulink
8.2 Simulation Results Analysis and Data Visualization
8.3 EV Design Optimization with MATLAB
8.4 Use of Optimization Based on Genetic Algorithms 8.5 Use of Multi-Objective Optimization.
8.6 Energy Efficiency Optimization.
8.7 Battery Life Optimization.
8.8 Sensitivity and Robustness Analysis.
8.9 Case Studies: Optimization of Different Design Parameters.
8.30 Conclusions and Next Steps in Analysis and Optimization.
4.4 Key Components and Architectures of EV Systems
4.2 Battery Modeling and Thermal Management
4.3 Simulation of Electric Motors and Controllers
4.4 Design and Analysis of Transmission Systems
4.5 Optimization of Energy Consumption and Range
4.6 Simulation of Vehicle Dynamics and Performance
4.7 Integration of Components and Subsystems in Simulink
4.8 Failure Analysis and Reliability in EV Systems
4.9 Advanced Simulation Tools and Techniques
4.40 Case Studies: Practical Applications in Industry
5.5 Fundamental Concepts of Electric Vehicles (EVs)
5.5 General Architecture of an EV
5.3 Main Components: Batteries, Motors, Controllers
5.4 Introduction to MATLAB/Simulink for Simulation
5.5 Simulation Workflows for EVs
5.6 Key Parameters and Design Considerations
5.7 Simplified Modeling of EV Systems
5.8 Creating a Baseline Model in Simulink
5.9 Preliminary Energy Performance Analysis
5.50 Introduction to Parameter Optimization
6.6 Modeling and Simulation of Electric Propulsion Systems
6.2 Selection and Analysis of Components for EV Systems
6.3 Design and Optimization of Batteries and Management Systems
6.4 Modeling of Electric Motors and Controllers
6.5 Analysis of Energy Efficiency and Performance of Electric Vehicles
6.6 Simulation of Propulsion Systems in MATLAB/Simulink
6.7 System Integration and Evaluation of Different Configurations
6.8 Failure Analysis and Safety in EV Propulsion Systems
6.9 Design of Control Strategies for Propulsion Systems
6.60 Cost and Life Cycle Assessment of Propulsion Systems
- Hands-on methodology: test-before-you-trust, design reviews, failure analysis, compliance evidence.
- Software (depending on licenses/partners): MATLAB/Simulink, Python (NumPy/SciPy), OpenVSP, SU2/OpenFOAM, Nastran/Abaqus, AMESim/Modelica, acoustics tools, planning toolchains DO-178C.
- SEIUM Laboratories: scale rotor bench, vibrations/acoustics, EMC/Lightning pre-compliance, HIL/SIL for AFCS, data acquisition with strain gauging.
- Standards and compliance: EN 9100, 17025, ISO 27001, GDPR.
Capstone-type projects
Admissions, fees, and scholarships
- Profile: Background in Computer Engineering, Mathematics, Statistics, or related fields; practical experience in NLP and valued information retrieval systems.
- Documentation: Updated CV, academic transcript, SOP/statement of purpose, project examples or code (optional).
- Process: Application → Technical evaluation of profile and experience → Technical interview → Review of case studies → Final decision → Enrollment.
- Fees:
- Single payment: 10% discount.
- Payment in 3 installments: No fees; 30% upon registration + 2 equal monthly payments of the remaining 35%.
Monthly payment: available with a 7% commission on the total; annual review.
Scholarships: based on academic merit, financial need, and promoting inclusion; agreements with companies in the sector for partial or full scholarships.
See “Calendar & Calls for Applications,” “Scholarships & Grants,” and “Fees & Financing” in the SEIUM mega-menu.
Do you have any questions?
Our team is ready to help you. Contact us, and we will respond as soon as possible.
F. A. Q
Frequently asked questions
Yes, we have international certification
Yes: experimental models, real data, applied simulations, professional environments, real case studies.
It is not mandatory. We offer leveling tracks and tutoring.
Completely. It covers e-propulsion, integration, and emerging regulations (SC-VTOL).
Recommended. There are also internal challenges and consortiums.
Yes. Online/hybrid modality with planned labs and visa support (see “Visa & Residence”).