Hybrid and Electric Vehicle Technology: Advanced
From engineer to EV systems architect: vehicle architecture, functional safety, digital twins, machine learning control, and a complete EV platform.
- Duration
- 8 weeks
- Level
- Advanced
- Content
- 48 lessons
- 8 modules · 16 h 10 min
- Certificate
- Included
- On completion
- Access
- Fee by email
What you'll learn
Who this course is for
- Intermediate level graduates ready to move into EV systems architecture roles
- Working EV and automotive engineers preparing for senior EV systems architect or controls engineer roles
- Engineers who want deep, hands on experience with functional safety and digital twins
- Anyone targeting senior EV systems architect, battery systems engineer, or vehicle integration lead career tracks
Skills you'll gain
This course includes
Course content
8 modules · 48 lessons · 16 h 10 min
EV systems architecture, advanced battery engineering, advanced controls and machine learning, functional safety and Model Based Design, thermal integration and vehicle networks, a minor project building a functional safety and verification package, digital twins prognostics and fleet systems, and a major project architecting a complete EV platform.
Requirements
- Completion of the Hybrid and Electric Vehicle Technology Intermediate level, or hands on experience modelling BMS, motor control, and vehicle energy management
- A computer capable of running MATLAB, Simulink, Simscape, and Stateflow
- Comfort with control systems, battery modelling, and vehicle networks concepts
About this course
Hybrid and Electric Vehicle Technology with Ucanly, Level 3 Advanced, takes you from engineer to EV systems architect. Built for practitioners who have completed the Intermediate level or have hands on experience modelling BMS, motor control, and vehicle energy management, this program goes deep into vehicle architecture, voltage architecture trade offs, and requirements engineering. You will build advanced battery models with Kalman filtering and degradation prediction, apply model predictive control and reinforcement learning to vehicle control, and understand the honest limits of AI in safety critical control. You will master ISO 26262 functional safety, hazard analysis and ASIL determination, and Model Based Design with MIL, SIL, PIL, and HIL verification, and in your minor project in week six, build a complete functional safety and controls verification package for an EV subsystem, with a Model Based Design workflow, MIL and SIL testing, an ISO 26262 aligned safety argument, and a defended verification case. You will then study vehicle thermal architecture, AUTOSAR software architecture, and digital twins, prognostics, and connected vehicle systems including V2G and grid integration. You will graduate having architected a full EV platform in your week twelve major project, with an integrated powertrain, BMS, thermal and energy management, a machine learning enabled feature, a safety and requirements framework, and digital twin validation, defended live to Ucanly mentors. This program is fully online, with all practical work delivered through industry standard simulation and Model Based Design tools that OEMs and suppliers genuinely use for production controls and safety development.
Earn a Ucanly certificate
Complete this course to earn a Ucanly certificate with its own page and QR code. Save it as a PDF, share its link, or add it to the certifications on your LinkedIn profile.
Frequently asked questions
It is recommended, but hands on experience modelling BMS, motor control, and vehicle energy management is sufficient to start.
Yes. Every module, lab, and project runs entirely online, with all practical work delivered through industry standard simulation and Model Based Design tools that OEMs and suppliers genuinely use for production controls and safety development.
Yes, your minor project is a complete functional safety and controls verification package for an EV subsystem, with a Model Based Design workflow, MIL and SIL testing, an ISO 26262 aligned safety argument, and a defended verification case.
A full EV platform architecture designed and validated end to end, with an integrated powertrain, BMS, thermal and energy management, a machine learning enabled feature, a safety and requirements framework, digital twin validation, and a defended architecture design to Ucanly mentors.