Electrochemical Virtual Sensor Development for Lithium-ion Batteries 

Application Deadline: In order to receive full consideration, the application should be received no later than June 30th, 2020. 

Duration: 3 years (European H2020 project INSTABAT, in final stages of signature)

Starting date: September / October 2020

Thesis grant: about 2,000 €/month (gross salary, Teaching Assistant supplement negotiable)

Location: Lyon (Rhône, France)

Primary fields: Control Systems Theory, Applied Mathematics 

Application fields: Electrochemistry, Electric Vehicles

Doctoral School: EEA, Université de Lyon, INSA Lyon (https://edeea.universite-lyon.fr, also available in English)

This proposed (36-month) PhD position in the Control Systems Department of Ampère Laboratory[1] at INSA Lyon is a part of the INSTABAT project[2], whose objective is to develop a proof-of-concept multi-sensor platform (or “lab-on-a-cell”) capable of real-time monitoring of key electrochemical and thermal variables inside a battery cell and of predicting their impact on related physicochemical degradation phenomena taking place. An important component of this platform will be a set of “virtual sensors” (more commonly known in the control-systems literature as “state observers”) that will allow the real-time estimation of key internal variables that cannot be directly measured. The information thus obtained should inform the Battery Management System (BMS) in order to improve the accuracy of available State of Charge, State of Health, State of Energy and State of Safety (SoX) indicators, and therefore adapt the charging and discharging strategies to improve the Quality, Reliability and Life (QRL) of the battery.

The retained candidate will have as main objective the development of state estimation algorithms for a class of infinite-dimensional systems (in this case, diffusive partial differential equations) representative of the electrochemical and thermal phenomena occurring inside the battery. In particular, the research will be oriented toward coupling thermal models and reduced Doyle-Fuller-Newman (or extended Single Particle type models), that are simple enough to run in real time but are able to perform adequately at high charge/discharge rates[3]. Some techniques that can be deployed include:

·      Backstepping transformations for partial differential equations[4]

·      Model reduction techniques (e.g. POD/Galerkin methods, finite differences, etc.)

·      Extended Kalman filter techniques / nonlinear observer techniques

·      Optimization and artificial intelligence techniques in general (e.g. convex optimization, machine learning, clustering techniques, etc.)

The candidate should have a strong foundation in mathematics and control systems. Strong skills in the following areas, or the ability to acquire them quickly, are highly desirable:

·      Applied Mathematics (Analysis, PDEs, etc.)

·      Optimization / AI techniques

·      Numerical methods

·      Programming using Matlab/Simulink

Furthermore, a working knowledge of basic electrochemistry, or the ability to acquire it quickly, will be required.

The successful candidate will be integrated into the Control Systems Department (AIS) of the Ampère Laboratory in Lyon and is expected to be able to evolve in a strongly interdisciplinary team including academic and industrial partners. As a key interlocutor in the European research program, the candidate should be capable of clearly communicating the developed algorithms and implementing them (or helping, as required, with their implementation) for integration in the proof-of-concept platform by the end of the project.

Some useful information about doing a PhD in France for foreign students: 

https://edeea.universite-lyon.fr/ed-160-eea/version-anglaise/navigation/international/foreign-phd-students 

https://www.campusfrance.org/en/FAQ-Doctorate-France-questions

Application:

Candidates have to send by email (see attached PDF file, if necessary) the following documents:

·      Curriculum Vitae

·      Cover letter

·      Master 1 and 2 transcripts (or latest two years of studies)

·      The name and contact information of 1 or 2 references (willing and able to provide a recommendation) 

[1] Ampère Laboratory is a research center bringing together researchers from the Université de Lyon, INSA Lyon, École Centrale de Lyon, Université Claude Bernard Lyon 1 and CNRS (UMR5005) http://www.ampere-lab.fr 

[2] Proposal 955930: “Innovative physical/virtual sensor platform for battery cell” (INSTABAT). Participating partners: CEA (FR), BMW (DE), CNRS (FR), Faurecia (FR), Infineon (DE), INSA Lyon (FR), Universidade de Aveiro (PT), Varta (AT).

[3] Moura, S. J., F. Bribiesca Argomedo, R. Klein, A. Mirtabatabaei and M. Krstic. Battery State Estimation for a Single Particle Model with Electrolyte Dynamics. IEEE Transactions on Control Systems Technology. Vol. 25, Issue 2. pp. 453-468. March 2017. doi: 10.1109/TCST.2016.2571663. [Preprint] [Electrochemical Model Simulator (S. Moura)]

[4] Krstic, M. and A. Smyshlyaev. Boundary Control of PDEs: A Course on Backstepping Designs. SIAM, Advances in Design and Control, 2008.