AI and the future of engineering education

1. Electrification, AI and the Future
of Engineering Education
Carlos Sanchis
Senior Academic CSE
@carsanbo
Sumit Tandon
Academic CSE Manager
@sumit77tandon

2. 2020 ASEE Survey for Skills Gaps in Recent Engineering Graduates
https://monolith.asee.org/documents/cmc/2020-SURVEY-FOR-SKILLS-GAPS-IN-RECENT-ENGINEERING-GRADUATES.pdf
Augmented Reality
Digital Twin
Artificial Intelligence
InfoSec
Robotics
Additive Manufacturing
IoT
Critical Thinking
Ethical Standards
Project Management
Economics and Business Acumen
Model-Based Systems Engineering
Simulation
Data Analytics Emotional Intelligence
Multidisciplinary Work
Self-Drive
Cultural Awareness
Hard Science and Engineering Fundamentals
Communication
Formulate and Solve Problems
Curiosity
Systems Thinking (80%)

4. Electrification
of Everything

5. Renewable Energies

6. Electric Vehicles

7. Electric Motors

8. Electronics Everywhere

9. Electrification
of Everything
Why is it happening?
What challenges is Industry facing?
How are engineers overcoming them?

10. Climate Change
InternationalEnergy Outlook 2019
https://www.eia.gov/outlooks/ieo/pdf/ieo2019.pdf
OECD: Organization for Economic Cooperation and Development
United States Environmental Protection Agency
https://www.epa.gov/ghgemissions/global-greenhouse-
gas-emissions-data#Sector

11. Need for Smarter, More Efficient Systems
Electricity use in the residential and
commercial sectors is predicted to
grow fastest in China, India, and other
countries with growing middle classes.
International Energy Outlook 2019
https://www.eia.gov/outlooks/ieo/pdf/ieo2019.pdf

12. Electrification
of Everything
Why is it happening?
What challenges is Industry facing?
How are engineers overcoming them?

13. Key Challenges in Electrification
▪ Dynamic Simulation
▪ Digital Control
▪ Supervisory Logic
▪ Rapid Prototyping
▪ Sensor Calibration
▪ Parameter Estimation
▪ Efficient Algorithms
▪ Controller Tuning
▪ Battery Modeling
▪ Safe Operation
▪ Aging Optimization
▪ BMS Development
Batteries Power Electronics Motor Control

14. Electrification
of Everything
Why is it happening?
What challenges is Industry facing?
How are engineers overcoming them?

15. Lightyear One
World’s First Solar-Powered Car
450 Miles on a Single Charge.
From Student Competition to Startup.

16. Key Challenges in Electrification
▪ Dynamic Simulation
▪ Digital Control
▪ Supervisory Logic
▪ Rapid Prototyping
▪ Sensor Calibration
▪ Parameter Estimation
▪ Efficient Algorithms
▪ Controller Tuning
▪ Battery Modeling
▪ Safe Operation
▪ Aging Optimization
▪ BMS Development
Batteries Power Electronics Motor Control

17. Voltage
time
Modeling Li-ion Battery Cells
R0
R1
C1
Em
Exponential relaxation
Instantaneous response
VΩ
Open circuit potential
Current
I0
discharge pulse
time

18. Equivalent Circuit

23. Equivalent Circuit Parameters
Lookup matrices as a function of…
• State of charge
• Temperature

30. Automatic C++ Code Generation
Generates equivalent C++ code to
program the real controller.

32. Autonomous
Systems

33. Autonomous Systems

34. Autonomous
Systems
Why is it happening now?
What challenges is Industry facing?
How are engineers overcoming them?

35. Why Now?
Artificial
Intelligence
Machine
Learning
Deep
Learning

36. Autonomous
Systems
Why is it happening now?
What challenges is Industry facing?
How are engineers overcoming them?

37. Key Challenges in AI
Model design
and tuning
Hardware
accelerated training
Transfer Learning
System verification
and validation
System
simulation
Data cleansing
and preparation
Simulation-
generated data
Domain expertise
Embedded
devices
Cloud/desktop
Data
Preparation
1
AI
Modeling
2
Simulation
and Test
3 Deployment
4

38. Autonomous
Systems
Why is it happening now?
What challenges is Industry facing?
How are engineers overcoming them?

39. 44
Subaru EyeSight
Detects obstacles, applies brakes, adjusts
cruise control, and stays in lane.

40. Automated Labeling Apps
AI
Modeling
2
Deployment
4
Data
Preparation
1
Simulation
and Test
3

41. AI
Modeling
2
Deployment
4
Data
Preparation
1
Simulation
and Test
3
Algorithms
Machine learning
Trees, Naïve Bayes, SVM…
Deep learning
CNNs, GANs, LSTM, MIMO…
Reinforcement learning
DQN, A2C, DDPG…
Regression
Linear, nonlinear, trees…
Unsupervised learning
K-means, PCA, GMM…
Predictive maintenance
RUL models, condition indicators…
Bayesian optimization
Pre-built models
Image classification models
AlexNet, GoogLeNet, VGG,
SqueezeNet, ShuffleNet, ResNet,
DenseNet, Inception…
Reference examples
Object detection
Vehicles, pedestrians, faces…
Semantic segmentation
Roadway detection, land cover
classification, tumor detection…
Signal and speech processing
Denoising, music genre recognition,
keyword spotting, radar waveform
classification…
…and more…

42. Leveraging the Larger AI Community
AI
Modeling
2
Deployment
4
Data
Preparation
1
Simulation
and Test
3

44. System Simulation
AI
Modeling
2
Deployment
4
Data
Preparation
1
Simulation
and Test
3

45. Deploy to Any Device with Zero Coding Errors
AI
Modeling
2
Deployment
4
Data
Preparation
1
Simulation
and Test
3
FPGA
CPU
GPU
Code
Generation

47. Systems Thinking
in the Classroom

48. Systems Thinking
in the Classroom
How can Systems Thinking be incorporated?
How can Students be prepared?
What if you have questions?

49. Cal State Los Angeles – Minidrone Project
https://tinyurl.com/3ws24bc7

50. Incorporating Systems Thinking: The technical aspects

51. Incorporating Systems Thinking: The non-technical aspects

52. Observations of student, faculty and the university
https://tinyurl.com/bdfmknb3
Dr. Michael Thorburn, Director, Senior Design Program, ECST:
“More and more design in industry is being done in software before engineers build
hardware prototypes, through software design and simulation, you can be confident that a
design will work before you start cutting metal. MATLAB isn’t the only tool we use, but it’s
very significant. It’s standard practice now in a variety of industries including aerospace,
aviation, and automotive. I encourage our students to use it as a way of differentiating
themselves with potential employers.”
Jocylene Arevalo, Mechanical Engineering Student,
Baja SAE Team Member, MATLAB Student Ambassador:
“…simulating before building is less risky and can save
companies millions of dollars. That was one of the reasons that
learning MATLAB was interesting to me.”

53. Systems Thinking
in the Classroom
How can Systems Thinking be incorporated?
How can Students be prepared?
What if you have questions?

54. Resources to consider:
https://github.com/mathworks/MathWorks-Excellence-in-Innovation

55. Self-Paced Online Training
Machine Learning
Onramp
Deep Learning
Onramp
MATLAB for Data
Processing and
Visualization
Machine Learning
with MATLAB
Deep Learning
with MATLAB
Circuit Simulation
Onramp
MATLAB
Onramp
Simulink
Onramp
Stateflow
Onramp
Control Design
Onramp
matlabacademy.mathworks.com

56. Freely Reusable Courseware
mathworks.com/academia/educators

57. Freely Reusable Courseware
mathworks.com/academia/educators

58. Freely Reusable Courseware
mathworks.com/academia/educators

59. Self-Paced Virtual Labs
mathworks.com/academia/courseware

60. Systems Thinking
in the Classroom
How can Systems Thinking be incorporated?
How can Students be prepared?
What if I have questions?

61. What if I have questions?
▪ Explore product pages and documentation
▪ Leverage the MATLAB user community
▪ Contact
– Technical Support
– Account Manager
– Customer Success Engineer

62. Thank you
© 2022 The MathWorks, Inc. MATLAB and Simulink are registered trademarks of The MathWorks, Inc. See mathworks.com/trademarks
for a list of additional trademarks. Other product or brand names may be trademarks or registered trademarks of their respective holders.