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MULTIivariable Environmental Control System

Periodic Reporting for period 3 - MULTIECS (MULTIivariable Environmental Control System)

Reporting period: 2020-10-01 to 2021-06-30

The goal of this project is the development of a Multivariable Control System (MCS) by means of non-linear control techniques, based on control-oriented thermodynamical models for the Electrical Environmental Control system (E-ECS). The focus will be on the use and adaptation of already existent real-time capable low-order models. In a second step, these models will be calibrated using test results from the Topic Manager (LTS). The subsequent MCS design will be performed in the Matlab/Simulink environment, in order to guarantee compatibility with LTS certification standards and processes. After successful simulation of the MCS implementation in Matlab/Simulink, an experimental validation of the MCS is aimed at the LTS’s facilities. The different objectives of the MULTIECS project are itemized as follows:

• Derivation of symbolic control-oriented models for the E-ECS.
• Efficient parameter identification of the nonlinear dynamic models to used in the MCS design aiming a small number of necessary test cases.
• Development of the multivariable optimal control structure in the Matlab/Simulink taking advantage of the non-linear control techniques.
• Assessment by simulations and experimental validation of the MCS.

More Electric Aircraft (MEA) is a tendency in the design of aircrafts, which is looking for reducing the complexity of the conventional aircraft, with the aim to improve the efficiency and reliability. The power used to operate an aircraft is divided in principal (e. g. propulsion)l and secondary power. The secondary systems are based on mechanical, hydraulic, pneumatic and electric mechanisms. For the case of Environmental Control System (ECS), as one of the secondary systems, the present pneumatic system is being substituted by an E-ECS, driven by electrical motors. The proposed approach uses gain-scheduling techniques to cope with the different flight modes, allowing for:

• An improvement of the transient thermodynamic performance
• A reduction of the power consumption

and guarantees a high passenger comfort.
Work performed, for each Work Package:

WorkPackage (WP) finished. The delivery of information by LTS has been completed: i) ECS modes including the electrical consumption optimization targets and the transient requirements; ii) current LTS Simulink model of the E-ECS; iii) equipment test data and system test data recorded on the ECS test rig; iv) requirements for control embodiment in the aeronautical controller. Also the studies with the LTS model to be carried out have been finished: i) specification of the relevant working points; ii) studies concerning model order reductions; iii) studies about real-time capability; iv) control allocation schemes.

Once the strategy for calibration of the LTS model was defined, the algorithms developed were used for the definition of the 1st test campaign, with a tool of prediction of the optimal nº of tests (UPC). In a parallel way, the tools for parameter identification of the control models are being developed by UROS. The corresponding automatic tools (calibration, optimization of nº points and parameter identification) are being developed, using simulation data of the LTS in absence of valid experimental information. Therefore, the tools of process of the experimental data (calibration and parameter identification) will be ready after the 1st test campaign.

This WP is mainly developed by UROS. The trade-off of the control theories (State-Dependent Riccati Equation, input/output linearization, Non-linear Model Prediction Control and linear control) is close to be finished. Also the definition of the control models is close to be finished (only the control models of the conditioning subsystem are pending). As the control models are the basis of the control theories to be applied, a special effort is being dedicated to this definition. Finally, it was suggested by UROS a decentralized control for the whole ECS.

This WP, related to coordination activities has mainly been done by the coordinator (UPC) as expected. The partners have contributed to this activity by the reporting and monitoring activity.
The main actions have been:
- Co-organize KoM, hosted at LTS facilities.
- Coordination and settlement of the Topic Manager Compliance Matrix and State-of-Work document.
- Website implementation.
- Dissemination: 2 papers submitted in international conferences.
- Follow-up conference call organization and generation of the corresponding MoM.
- Monitoring and fostering of the project activities. Implement flexible workplan alternatives to reduce the impact of project unexpected difficulties.
- Reporting P1 activities, coordinating the input given by the partners.
The present solution for the ECS involves a pneumatic circuit with a single-input single-output (SISO) controller. However, the desired thermal comfort according to cabin and cockpit requirements could not be guaranteed in all situations. Moreover, the whole system still has a large potential regarding energy optimisation. In the MEA, the E-ECS can be controlled by a MCS, where the design is explicitly based on the combined minimization of control errors and control effort. This system will take advantage of the full potential of optimizing the electrical consumption by ensuring an optimal performance of all the components.

In the MULTIECS project, the MCS takes advantage of non-linear control techniques. This appproach represents a powerful and flexible model-based design for nonlinear systems, such as the E-ECS, with several active components for control. Moreover, MCS are capable of addressing given cross-couplings properly, therefore are especially suitable for maximizing the performance of these complex systems under dynamic working conditions.

Another challenge is the reduction of the complexity. By means of corresponding cost functions involving weighting matrices for quadratic terms regarding states and control inputs, individual design specifications can be met and trade-offs can be found. Moreover, an extension towards variable weighting matrices, which may also depend on either states or system parameters, becomes possible. Thereby, a situation-dependent close-loop dynamics can be realized and alternative operating modes can be handled efficiently. As a results, this leads to a systematic gain-scheduled controller parametrization as well as a simplified implementation.

Concerning calibration methods, the main requirements are on the one hand, a reduction of the testing time and a small number of test cases. On the other hand, sufficiently accurate design models are needed. The MULTIECS project addresses this challenge by means of symbolic control-oriented models that cover only the dominant system dynamics. Efficient least-squares techniques will be used to parametrize the nonlinear models properly. This approach will imply the starting point for develop more advanced embedded physical models by integrating HPC to real-time control for other applications in the next future.

The compatibility with LTS certification standards and processes of the present development is guaranteed by using Matlab/Simulink from MathWorks. The method of development is flexible and adaptable to other electrical air conditionning packs with a similar architecture. Thereby,its potential market is hugely increased. This latter characteristic increase the potential applicability of the proposed MCS solution.