Mehdi Abbes

Pseudo Bond Graph Modeling and Experimental Investigation of Thermal Transfers Inside a Household Refrigerator

This paper proposes a pseudo bond graph model of thermal transfers by natural convection inside a household refrigerator. It has two inputs: the ambient temperature and the temperature at the level of the evaporator wall. The latter assesses the functioning of the compressor cycles. A performance comparison, with the experimental data, was carried out in order to verify the model, in which, real measurements are used to modulate the evaporator temperature source. The simulation results show the effectiveness of the proposed approach.

FPGA implementation of predictive control

In this paper, we propose an implementation of a synthesizable VHDL program of generalized predictive control (GPC) without constraints on a map XC3S700A Xilinx Starter Kit using the Xilinx ISE 10.1 software. The control strategy was applied to a second order state system. The VHDL language was used as a programming tool. Real variables were described with the fixed-point representation to overcome the overflow problems during the computations in the VHDL program. The use of FPGA circuits presents a good choice regarding to the problem of computation time encountered in predictive algorithms. A GPC Matlab program was also implemented in order to make a performance comparison. The simulation results show a good set-point tracking.

Solutions based on renewable energy and technology to improve the performance of refrigeration systems

This paper presents a review of recent studies interesting in improving the energy efficiency and cooling quality of refrigeration systems, especially, household refrigerators, air conditioners, and cold storages. They proposed solutions based on renewables such as solar, geothermal, and natural cold through designing advanced plants. Their overall improvement in energy management could bring savings of up to 95% in appropriate conditions and according to the structure of the refrigeration installation. The paper also gives statistics about the energy consumption of refrigeration systems and the interest of using renewables in this field.

Temperature control in a cavity of refrigeration using PI controller and predictive control

A PI controller and a generalized predictive control strategy of the temperature inside a cavity of refrigeration are proposed, using Matlab/Simulink environment. The control strategies were applied to a third-order discrete state space system, which computes the internal air temperature according to the temperature at the level of the evaporator exchanger, under the influence of the ambient temperature. The system was obtained by linearization of a pseudo bond graph model of thermal transfers inside the refrigeration cavity. The simulation results were compared to those of the pseudo bond graph model for a classical thermostatic control. The used control strategies allowed an average energy saving of about 70% compared with the conventional on/off controller.The predictive control was more efficient than the PI controller of 23.33 %.

Pseudo bond graph model of a thermo-hydraulic system

The paper presents a pseudo bond graph model of a thermo-hydraulic system which is composed by two warm and cold water pipes, a plastic tank and an evacuation pipe. This model is designed on 20sim software and it allows varying the temperature, inside the tank, by acting on the mass flows of the warm and cold water, as well as on the evacuation pipe. A simulation is done for constant and variable water mass flows to show the efficiency of this bond graph model.

Arnoldi model reduction for switched linear systems

In this paper we present a new method of reduction for large-scale switched system, which is an important class of hybrid and non linear systems. In this work, we focus on linear switched systems. This new method is based on the generation of Krylov subspace by the use of the Arnoldi algorithm, which is numerically efficient and applicable for any order, from which we solve the problem of H∞ model reduction. We take one example to evaluate this method.

Cooling performance and energy saving of a refrigeration cavity supported by an outside cold air flow controlled by a PID controller

This paper aims to prove the efficiency of using the free, abundant cold air flow stemming from the outside in high altitude to enhance the cooling inside a refrigeration cavity and to reduce the energy consumption. The cold air flow is spread out inside a cavity covering the side wall of the appliance and, which is connected to the inlet and outlet conducts. For that purpose, a Simulink model is proposed to model this installation. The internal temperature is computed according to the evaporator temperature and the outside cold air flow, which is also computed according to the outside temperature. The simulation results show that when the internal temperature is higher than the desired one and the outside temperature is low enough, the use of the controlled cold air flow as a second cooling source allowed to speed-up the cooling inside the refrigeration cavity of about 36.21 % and to reach an energy saving of about 36.23% compared with the classical thermostatic control. When the internal temperature drops below the desired one, the appliance did not consume any energy.

Fractional order model of a greenhouse

A fractional order model that describes thermal and moisture behaviors in the greenhouse was done. In modeling the greenhouse many authors use a simple model of soil that neglect the heat / mass coupling, furthermore they use the discretization techniques for solving the heat conduction equation leading to a very high order model, this causes problems when applying a control and requires a high time in the simulation. Several studies [3], [6] have proved that the fractional modeling offer better results and with less parameters when modeling the thermal system. The new contribution of this article is to put a greenhouse model of fractional order which takes account the heat / mass coupling in modeling the soil with the assumption that diffusion coefficients are constant. The verification of the new fractional model is done by a base of experimental data that presented in [2].

Pseudo Bond Graph Model of Thermal Transfers Supported by an Outside Cold Airflow of a Refrigerator to Improve Its Performance

This paper aims to prove the efficiency of using the naturally free and abundant cold airflow to improve the cooling inside a household refrigerator and to reduce the energy consumption in Nordic a...

SVD-AORA Model Order Reduction Method for Large-Scale Dynamic Linear Time Invariant System

In this paper we present a joint model for order reduction for dynamic linear time invariant (LTI) system, which we call SVD-AORA (Singular Value Decomposition-Adaptive Order Rational Arnoldi). The SVD-AORA method is an extension of the SVD-Krylov based method. It is based on linear projection using two projection matrices (V and Z). The first matrix V is generated using the Krylov technique through the AORA method, the second matrix Z is generated using the SVD technique by the resolution of the Lyaponuv equation. After the resolution of the Lyaponuv equation, the solution obtained (The gramian observability matrix go) is decomposed using the SVD technique and thus we obtain the second projection matrix Z. The use of the AORA method enhances the numerical efficiency thanks to its relative lower computation complexity and the use of the SVD technique preserves the stability of the reduced system. The proposed method gives a reduced order model asymptotically stable, captures the essential dynamics of the original model and minimizes the absolute error between the original and the reduced one. The results of the proposed method are compared with other popular approach of order reduction in the literature which is the SVD-Krylov method. The reduced systems obtained by the proposed method have better performance compared to SVD-Krylov method. The method is explained through two numerical systems of different order. Introduction Technological world, physical and artificial processes are mainly written by mathematical models which can be used for simulation or for control. Among these models the LTI of high order. However, these high order models are difficult to manipulate and analyze because of the fact that the resolution of these models is indeed very demanding in computational resources, storage space, and mainely in CPU time. Hence the necessity of model order rection technique.. In the literature there exist different reduction methods of linear time invariant system (Arnoldi, Lanczos [1, 2, 3, 4],Rational Arnoldi [5],Rational Lanczos [6, 7], AORA [8], AOGRA [9], AORL [10], PRIMA [11],...); which performance differantly. Among these performances we can mention: • A significantly reduced number of variables or states (required for description of a given model) compared to the original model, • The simulation should be quick and does not require large memory space, • The computational complexity associated with the evaluation of the reduced model should be significantly lower than the original model, • Stability of reduced model must be guaranteed, • Minimization of error between the original model and reduced one. To Bring this performances, we depict in this paper the SVD-AORA method. This paper in organized as fol-