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Department of control engineering and system analysis

Person in charge of the Unit : Oui

The research activities of the SAAS group are essentially oriented in two directions:
- Supervision and fault diagnosis of technical systems based on mathematical models
- Advanced control of nonlinear dynamic system subject to constraints, with emphasis on reference governor methods
The developed methods are applied to a wide range of areas including:
- Electric energy production, distribution and storage
- Mechatronics (UAVs and robotics)
- Industrial processes


Multi-sensor battery monitoring

The project aims at improving the aging modelling and monitoring of large lithium-ion batteries in the form of pouch cells, by exploiting additional measurements besides the classical cell voltage, current and surface temperature.  Fiber Bragg grating (FBG) sensors will be used to record local temperature and strains at the surface of the battery while the so-called battery cell management unit (CMU) will provide electrochemical impedance spectroscopy (EIS), humidity and gassing measurements.  Battery aging campaigns will be performed, in which the above measurements will be recorded, and regular performance test will provide capacity and power fade estimates.  Next, the electrical, electrochemical, mechanical and thermal measurements will be combined in order to model and predict capacity and power fade.  The most relevant measurements or grouping of measurements will be determined by dimensionality reduction methods and appropriate black box models will be identified.  The merging of time and frequency domain data will be performed in two ways. Either a single model will be fitted with both types of data, or estimates determined from each data type will be merged, and the best option will be retained.  The outcome of the project will include 1) a data base of well documented multi-physical measurements suitable for battery aging studies, 2) a selection of the most relevant measurements for capacity/power fade monitoring and 3) a systematic approach for modelling and predicting these phenomena.

MONISA - Health monitoring of an EMA for aircraft primary flight surface control

The trend is to replace the hydraulic actuators by electromechanical actuators (EMAs) in aviation. This structural change would allow cancelling the overall hydraulic circuit on board and thus decrease the maintenance needs, the energy consumption and the aircraft weight. MONISA aims at designing, implementing and validating a monitoring system for EMAs used in aircraft flight surface control.  Such a system will allow keeping an identical level of safety and availability for the EMAs as for hydraulic actuators by following their health status. It should be able to detect in a premature way any fault occurrence on the EMAs and follow its temporal evolution. In that way maintenance operations can be performed in due time to avoid that the degradations lead to a functional failure of the actuator. Furthermore, the monitoring system must have a very low false alarm probability in order not affect aircraft availability.  

Optimization and monitoring of environmetally friendly battery packs

The project aims at developing safer, long lasting and environmentally
friendly lithium ion batteries for use in stationary storage applications. The
targeted batteries are made of LTO/LFP electrode materials coated onto
current collectors via a novel aqueous preparation pathway. These 
chemistries are indeed known to be more stable and safer than others.
However, there is no guarantee that the manufactured battery is the safest
or the one with the best performance among different possible designs.
Moreover, currently there is no way to track the progression of its internal
state as the battery is operated. These two issues can be addressed
through the combination of electrochemistry, mathematical modelling and
control theory, three domains of expertise covered by the two partners.
Three lines of research will be pursued: the optimal design of a battery cell,
the study and modelling of aging for such a cell, and the state monitoring of
a battery pack. The battery design optimization seeks to improve the
battery performance through appropriate sizing. The associated challenges
include the choice of relevant design criteria and degrees of freedom to be
optimized. The optimized battery design will be experimentally validated by
building the cell and verifying the resulting performance index. The aging
model will exploit long term cycling experiments to determine aging as a
function of the operating conditions. Such information will be used in the
battery pack state monitoring system that aims at estimating the state-of
charge and state-of-health of the constituent battery cells. These packs
arise when series/parallel arrangements of cells are considered in order to
meet voltage/power requirements.


Due to the expensive nature of rockets, a major challenge consists in reducing their costs. Launchers in particular are quite expensive and the majority is expendable. Market competition brought aerospace enterprises to search for new ways to cut prices, notably by reusing their launch systems. During each stage of ascension, specific boosters constituting the rocket are decoupled, generally left to fall into the sea. One of the reason why launchers are not reused comes down to the lack of knowledge on the health status of their components, including their actuators. The latter typically serve to orientate the nozzle for propulsion. In case of reusable launchers, additional electromechanical actuators (EMAs) can be included to control stabilizing fins and to deploy legs during descent.

The project aims at developing a health monitoring system for high performance electromechanical actuators to be used for reusable launchers. It is part of a WIN4EXCELLENCE programme involving 30 PhD students and dealing with innovative tools for earth observation and reusable launchers. An hybrid fault diagnosis approach is considered for detecting both electrical and mechanical faults, combining a physical model with data-driven techniques. This methodology will require data on both healthy and faulty EMAs. To produce synthetic data on faulty scenarios, the first step consists in establishing a physical-based simulation of the EMA’s health status. The second step is about realising the fault diagnosis. System states will be evaluated through an observer, potentially a Gaussian process.

Optimal power dispatching in offshore wind farms ensuring power reserve for frequency control and load mitigation (PhairywinD)

This research project is part of the  Belgian PhairywinD project, which aims to develop the current and the future offshore wind farms in a multi-disciplinary framework. The ability to participate in the frequency regulation and provide ancillary services to the TSO (Transmission System Operator) is one of the present offshore wind farm challenges. The goal of this research is to further investigate how wind farms can achieve this goal at best by taking into account wake effects, load mitigation and active power reserve in the dispatching of the active power set points to the turbines. The control strategy will be based on the following modules : a module estimating the total power available in the immediate future, a module deducing the plant wide power reserve needed to ensure proper frequency regulation, and a module performing the optimal power dispatching.  The developed control strategy will be implemented and validated in simulation using software like and SOWFA.