Skip to main content Skip to navigation

ES2H6-15 Future Automotive Mobility

Department
School of Engineering
Level
Undergraduate Level 2
Module leader
Emma Rushforth
Credit value
15
Module duration
10 weeks
Assessment
50% coursework, 50% exam
Study location
University of Warwick main campus, Coventry

Introductory description

There are 3 strands to future automotive mobility: Connected Autonomous Vehicles (CAVs), Electric Vehicles (EV's) and Mobility-as-a-Service (MaaS). The combination of these three key technology-driven disruptive trends is introducing unpresented changes to the automotive sector. This module will provide the key knowledge and understanding to support automotive engineers in the future.

Module aims

Future automotive mobility aims to introduce the students to the key challenges associated to smart, connected and autonomous electric vehicles: SAE levels of autonomy and their implications on safety; robustness of embedded systems; environmental perception; connectivity and communication infrastructures; new mobility models; battery technologies for EV's.
This module aims to provide the students with knowledge associated with current and future technical challenges of smart, connected and autonomous vehicles and their importance for electrification.

Outline syllabus

This is an indicative module outline only to give an indication of the sort of topics that may be covered. Actual sessions held may differ.

Connected Autonomous Vehicles (CAVs): perception sensors, sensor fusion, machine learning & probabilistic techniques for CAV, wired and wireless communications (e.g. 5G) for CAV, CAV security risks
Electric Vehicles (EV's):battery management, battery manufacture, battery recycling, battery materials mining, battery lifecycle.
Mobility-as-a-Service (MaaS) -MaaS schemes, vehicle management, public transport integration, MaaS regulations.

Learning outcomes

By the end of the module, students should be able to:

  • Critic the limits of the performance of different automotive perception sensors. (C1, M1)
  • Understand the limits of machine learning and sensor fusion in the context of safe Automated Vehicles. (C1, M1, C2, M2, C4, M4, C9 M9)
  • Understand the limits of wired and wireless communication technologies in the CAV context particularly security risks. (C1, M1, C10, M10)
  • Critic mobility-as-a-service systems. (C4, M4, C7, M7(D))
  • Analyse well-established battery technology, lifecycle and infrastructure implications of electric vehicle use. (M1, C1, C4, M4, C7, M7)

Indicative reading list

"Automated vehicles and MaaS : removing the barriers ", Williams Bob. Hoboken, NJ : Wiley, 2021, 978-1119765349 (epub)
"Advanced Battery Materials", C. Sun. John Wiley & Sons, 2019. ISBN: 9781119407553
“Introduction to autonomous mobile robots”, Siegwart, Roland, Nourbakhsh, Illah R., (2nd Edition), 2011, 978-0262015356, TJ 211.S4
“Probabilistic Robotics”, Thrun, Sebastian, Burgard, Wolfram, Fox, Dieter, 2005, 978-0262201629, TJ 211.T575
"Infrastructure Wi-Fi for connected autonomous vehicle positioning : a review of the state-of-the-art", Adegoke, Elijah I., Zidane, Jasmine, Kampert, Erik, Ford, Col R., Birrell, Stewart A. and Higgins, Matthew D. (2019) Infrastructure Wi-Fi for connected autonomous vehicle positioning : a review of the state-of-the-art. Vehicular Communications, 20 . 100185. doi:10.1016/j.vehcom.2019.100185

Subject specific skills

Knowledge and understanding of the need for a high level of professional and ethical conduct in engineering and the use of technical literature, other information sources including appropriate codes of practice and industry standards.

Transferable skills

Be professional in their outlook, be effective communicators, and be able to exercise responsibility and sound management approaches.
Communicate (written and oral; to technical and non-technical audiences)
Exercise initiative and personal responsibility, including time management, which may be as a team member or leader

Study time

Type Required
Lectures 40 sessions of 15 minutes (7%)
Seminars 10 sessions of 1 hour (7%)
Fieldwork 5 sessions of (0%)
Private study 130 hours (87%)
Total 150 hours

Private study description

130 Hours of student self-guided study to prepare for assessments. Guidance on topics to be studied is provided during lectures (with some extra contents on Moodle) and assessment instructions.

Costs

No further costs have been identified for this module.

You must pass all assessment components to pass the module.

Assessment group C
Weighting Study time Eligible for self-certification
Assessment component
Mini Design Portfolio 50% Yes (extension)

Design portfolio 3000 words

Reassessment component is the same
Assessment component
Online exam 50% No

QMP 1 hour long

~Platforms - AEP, QMP, Submission Through Tabula Assignment Management

Online examination: No Answer book required
Students may use a calculator
Engineering Data Book 8th Edition

~Platforms - AEP,QMP

Reassessment component is the same
Feedback on assessment

Written comments and electronically marked-up assignments for the design portfolio.
Cohort level feedback on examinations

Past exam papers for ES2H6

Courses

This module is Optional for:

  • Year 2 of UESA-H335 BEng Automotive Engineering
  • Year 2 of UESA-H336 MEng Automotive Engineering