At a Glance
- Tasks: Develop AI-driven electromechanical braking systems for electric vehicles.
- Company: Collaborate with a leading international automotive manufacturer.
- Benefits: Tax-free stipend of £21,805 and a £5,000 research training grant.
- Other info: Opportunity for real-world impact and collaboration with industry experts.
- Why this job: Join a cutting-edge project that shapes the future of EV technology.
- Qualifications: 2.1 or 1st degree in relevant engineering or computer science fields.
The predicted salary is between 21805 - 21805 £ per year.
Project Overview
One of the current challenges in electric vehicle (EV) technology is the development of electromechanical braking (EMB) systems to replace conventional hydraulic brakes and integrate them with primary regenerative braking. EMBs are highly sensitive to EV harsh operating conditions. This project addresses this challenge by developing AI-based EMB clamping force estimators and robust control algorithms, validated in real-time simulations and experimentally in collaboration with industry.
The project looks at the development of electromechanical friction wheel braking (EMB) systems to replace existing hydraulic brakes. This reduces weight, maintenance costs and environmental pollution. Critically important, this enables the development of faster friction (secondary) braking systems that meet Level 5 EV automation requirements. The EMB consists of an electric motor, a power electronic converter, a gear and a motion conversion mechanism to press the brake pads against the wheel disc and to generate the clamping force (CF) to be controlled. Onboard CF direct measurement is impossible. CF tracking control includes three stages: clearance elimination, clamping and release. In industry, it is implemented via three-loop CF cascaded control.
Project Objectives
- Robust and fault‑tolerant CF estimator that over‑performs Level 5 EV automation expectations under EMB parameter variations and sensor malfunctions.
- Robust and efficient CF control with Level 5 EV automation tracking accuracy under harsh operating conditions, and automated identification algorithms for self‑commissioning.
The project will be done in collaboration with an international automotive manufacturer whose R&D Centre is located in the UK. Two industrial supervisors will ensure that the estimation and control algorithms comply with automotive standards and are compatible with automotive protocols, lead EMB test bench development and provide the necessary training to the PhD student. HiL simulations will be conducted on the dSpace platform and the company’s electronic control unit.
Scholarship
The award will cover the UK tuition fee level, plus a tax‑free stipend, currently £21,805, paid at the prevailing UKRI rate for 3.5 years of full‑time study. This award also includes a £5,000 research training support grant.
Eligibility
This studentship is available to home students only. Home students are eligible to apply. The candidate should have a 2.1 or 1st Bachelors or Masters degree in Electrical or Electromechanical or Electronic Engineering, Mechatronics, Control, Mechanical or Automotive Engineering, Computer Science, Applied Mathematics or other related Engineering disciplines/Physics.
How to Apply
Candidates should submit an expression of interest by sending a CV and supporting statement outlining their skills and interests in this research area via the 'Apply' button above. If this initial application is successful, we will invite you to submit a formal application. Candidates must fulfil the University of Warwick entry criteria and obtain an unconditional offer before commencing enrolment. Should your application for admission be accepted, you should be aware that notification of acceptance for the PhD does not constitute an offer of financial support. Successful scholarship candidates will receive an official communication from the School of Engineering to confirm their award.
PhD: AI‑Driven Electromechanical Braking Systems in Coventry employer: University of Warwick
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