PhD Position « Control and optimization of zinc-air flow battery integrated with zinc regenerative system »

Control and optimization of zinc-air flow battery integrated with zinc regenerative system

Date limite de candidature : 30/11/2021
Date de début : 01/02/2022
Date de fin : 31/01/2025

Pôle : Automatique et systèmes
Type de poste : Thèses
Contact : Cristina VLAD (cristina.vlad@l2s.centralesupelec.fr)

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 PHD Position

Control and optimization of zinc-air flow battery integrated with zinc regenerative system

Supervisors:

Place of work: L2S (Laboratoire des Signaux et Systèmes), UMR 8506 Université Paris-Saclay, CNRS, CentraleSupélec, 91190 Gif-sur-Yvette, France

Type of contract: CDD (36 months, full time)

Deadline for applications: November 30, 2021

Duration: February 01, 2022 – January 31, 2025

 

Keywords: battery management system, modelling of energy storage systems, system identification, learning and control

 

Project description

 

The primary objective concerns the improvement of the operations by the development of a dynamic model of zinc-air flow batteries (ZAFBs) integrated with zinc regenerative system. The developed model will be assessed through experimental data. The effects of different operating conditions will be analyzed and monitoring and performance-assessment modules will be designed including fault detection and failure diagnosis capabilities.

Secondly, the integration of the ZAFB within a power grid will represent a subject of interest. Indeed, battery and energy management systems (BMS and EMS) are required to integrate ZAFB into a power grid for reasons related to cost, size, safe operation and overall management issues. A BMS handles the charge/discharge rates of the battery according to its state of charge (SOC), the power load demand and other variables such as cell voltage, current, and electrolyte composition. The EMS supervises the energy flow between multiple power supply/storage systems and ensures that the demanded power load is delivered on time while considering the efficiency optimization of the overall system and the power fluctuation within the grid. Control and supervision systems for ZAFB applications need to be designed to ensure an optimal use of the energy stored and to prevent inflicting damage to the battery system. By optimizing the battery discharge rates and zinc regeneration conditions the loss of capacity is prevented, the battery performances and its life cycle are improved.

 

Context

 

The project aims to develop a theoretical framework and associated numerical methods for mathematical modeling and identification of energy storage systems (ESS). Aside the fundamental characterization of this class of nonlinear dynamical systems, the objective is to design algorithms for automatic control and optimization for the zinc-air batteries, one of the ESS which are currently considered among the most promising technology. Our interest is oriented to this particular chemistry due to the high specific energy capacity, the widespread occurrence of zinc in nature, its non-toxicity and low cost, the air-zinc power technology has high potential and can find successful applications as storage systems for renewable energy sources or mobility.

The project aims to promote technologies and practices for effective integration of Renewable Energy Sources (RESs) to the grid through efficient and sustainable system design and management considering electrical energy storage (EES). This allows a reliable, cost-effective and efficient integration (off-grid or on-grid) of RES and facilitates the higher penetration of RES in the energy mix, which can result in emissions reduction and enhanced energy security. Additionally, it provides opportunities for small RES power producers to participate in energy markets.

Recently, despite the active development of prototypes of air-zinc batteries (mostly accompanied by applied chemical research papers), there is a fairly small number of works devoted to aspects of their mathematical modeling and optimization in view of operation. The goal of this project is to identify the dependence of the dynamics of the battery on its state of charge, discharge current, load, temperature and other macro parameters, as well as to determine the optimal operating conditions of both a single cell and a system of cells connected in parallel. The central tasks of the project are the analysis of the dependence of the inflection point of the discharge curves on the discharge current, the assessment of the state of charge and potential difference at the terminals of the air-zinc battery and the use of these signals in order to build a mathematical model mixing both first principles and the features of the real-world experiments. The mathematical model needs to offer the flexibility to adapt in real-time the previously estimated parameters according to the online measurements.

 

Objectives

 

We plan to develop a new parametric mathematical model of the dynamics of the zinc-air battery, considering its electrochemical properties, and an algorithm for identifying its parameters. Also, based on this model, the optimal control for both single cell and system of cells connected in parallel will be constructed. The system identification will use the data already obtained by the international team of collaborators and new experimental data to be recorded according to the identification protocols developed within the current project. These experimental data will be collected using the zinc-air battery prototype, recently made available in the Laboratory of Signals and Systems of CentraleSupelec.

The research studies conducted during the thesis are expected to address the following tasks:

 

Methods

 

The scientific novelty of the proposed project is driven by new research technology (ZAB). Its mathematical modeling problem has not yet been addressed in the literature and by its intrinsic properties promise to concentrate the generic elements to leverage understanding on the energy storage systems in the large. In this regard, in order to achieve the goal formulated within the framework of the project, it will be necessary either to substantially modify the standard modeling methods used to analyze alternative power sources, or to develop new generic approaches that will bring mathematical modeling and optimization of ESS to a significantly new level.

Zinc-Air cell discharge modeling: The first stage will be devoted to the construction and identification of a mathematical model for the dynamics of a ZAB cell. Is worth to be mentioned that approaches traditionally used to model and identify the parameters of other types of energy sources cannot be successfully used for ZAB case due to the specific electrochemical properties of the zinc-air technology (some of the particularities being the stiff dynamics and the weak observability of internal state as a result of the flat dependence in between the capacity and the open-circuit-voltage). In this regard, within the framework of this stage, it is planned to develop a generic approach combining modern data-driven technologies and traditional first principles modeling (mainly Coulomb counting). This approach can find wide application in modeling various physical processes based on accumulated experimental data (the strong observability, if available, being used only to enhance the structural properties).

Predictive control and optimization: The second stage of the project will concentrate on the problem of optimal control in real-time. The goal here is to maximize the battery state of power (SOP) by adjusting the optimal combinations of the discharge current and the output voltage of the loaded battery in concordance with the required references and performances all by including the safety constraints. The real-time control and the battery management will build on a model-based approach, fully exploiting the explicit prediction model obtained in the previous stage.

Battery management: The third stage of the project will focus on the scale-up procedure and the elaboration of a strategy for optimal control of the system consisting on air-zinc cells connected in parallel using the models developed in the previous stages, as well as the formation of a methodology for assessing the overall state of the battery, monitoring its performance and the real-time faults diagnosis. This stage also implies the development of a strategy for balancing cells’ capacity by redistributing the current between them and adjusting the laws governing the discharge process. Solving these problems will require the use of adaptive optimal control methods, potentially in a distributed framework.

 

Practical information

The PhD project will take place in L2S. It will involve both theoretical and practical developments. On the practical side, this is mainly related to the acquisition of data from energy storage systems and the on-line monitoring and optimization of their control signals.

The main valorization will be done through publications. Upon the development of a battery management system, its development on an industrial scale can be discussed according to the evolution of the research.

For the construction of zinc-air batteries and the chemical insights on the project, the PhD student will be in contact with colleagues from the Chulalongkorn University in Bangkok who are able to update the existing technology according to this project of BMS development.

Qualifications

The candidate should have a solid background in model identification, very good English speaking and writing skills, good communication skills, a master (or equivalent) degree in control engineering, mathematical physics, applied mathematics.

Experience with numerical methods and optimization is a plus. Matlab experience is welcomed.

To apply: please send a detailed curriculum vitae, the academic record, a motivation letter and the names and contact details of 2 referees to Sorin Olaru, Pedro Rodriguez and Cristina Vlad {sorin.olaru, pedro.rodriguez, cristina.vlad}@l2s.centralesupelec.fr

 

References

 

[1] W. Lao-Atiman, K. Bumroongsil,A. Arpornwichanop, P. Bumroongsakulsawat, S. Olaru and S. Kheawhom. “Model-based Analysis of an Integrated Zinc-Air Flow Battery/ Zinc Electrolyzer System,” in Frontiers in Energy Research, 7,15, 2019.[2] W. Lao-Atiman, S. Olaru, A. Arpornwichanop and S. Kheawhom. “Discharge performance and dynamic behavior of refuellable zinc-air battery,” in Scientific data, 6(1), 1-7, 2019.[3] S. Olaru, A. Golovkina, W. Lao-Atiman and S. Kheawhom. “A Mathematical Model for Dynamic Operation of Zinc-Air Battery Cells,” in IFAC-PapersOnLine, 52(17), 66-71, 2019.[4] A. Golovkina, S. Olaru, D. Ovsyannikov. “A Robust Optimization Model for the Radioactive Waste Transmutation in ADS,” in 2019 6th International Conference on Control, Decision and Information Technologies (CoDIT), pp. 703-708, 2019.[5] A. Abbasi, S. Hosseini, A. Somwangthanaroj, R. Cheacharoen, S. Olaru and S. Kheawhom. “Discharge profile of a zinc-air flow battery at various electrolyte flow rates and discharge currents,” in Scientific data, 7(1), 1-8, 2020.[6] W. Lao-Atiman, S. Olaru, S. Diop, S., Skogestad, A. Arpornwichanop, R. Cheacharoen and S. Kheawhom. “Linear parameter varying model for a refuellable zinc–air battery,” in Royal Society Open Science, 7(12), 201107, 2020.