Integrated Groundwater Flow Modeling for Managing a Complex Alluvial Aquifer Case of Study Mio-Plio-Quaternary Plain of Kairouan (Central Tunisia)

In central Tunisia, anthropic activities, such as groundwater abstraction for irrigation, have resulted in excessive groundwater level declines of the Mio-Plio-Quaternary aquifer hosted in Kairouan Plain. Besides, the two dams El Houareb and Sidi Saad’s impoundment since the 1980s has deeply modified the natural process of aquifer recharge. Hence, some studies claim the dam’s instauration of this groundwater depletion; however, some other studies attribute this critical situation to an issue of groundwater management. A multidisciplinary study was carried out to retrace the groundwater flow dynamics for 48 years before and after the dams’ erection and to understand the main factors causing the groundwater depletion. Hence, a conceptual model was developed based on gathering all available data from 114 borehole logs, 10 seismic lines, and 08 petroleum wells. Based on this reconstructed geometry, the groundwater head was simulated using the numerical code Modflow. The model was calibrated in steady-state with reference to the piezometric levels measured in 1969 and in the transient state for the period 1970–2017 and validated for the period 2007–2017. The outputs of the calibrated model show a relevant finding of the decrease of the inflows coming from the rivers’ beds (Zeroud and Marguellil) from 1990 to 2017 by 48%; yet, the pumping rate has increased by 119%. The simulated scenario without dams and maintaining the same withdrawals has shown a groundwater level rise downstream of the plain; yet, in its upstream, the depletion was less intense compared to the current model. However, the case of doing without dams and raising withdrawals from the aquifer has generated a huge decline reaching 22 m near Draa Affane

Sizing and Control of Onboard Multisource Power System for Electric Vehicle

International audienceThis paper deals with the sizing and control of a fuel cell based hybrid power supply used in vehicular applications. The system consists of a fuel cell, a battery and a pack of ultra-capacitors connected to three DC-DC converters. The proposed approach takes into account dynamic constraints and energetic capacity limits of the power sources by considering a filtering based energy management strategy and energetic characteristics of the used technologies. The sizing solutions are computed for two different driving cycles and then the systems are modeled and simulated using MATLAB/SimPowerSystems. The obtained results are given and discussed. Index Terms-Fuel cell hybrid vehicle, electric storage systems, sizing, energy management strategy

New LiFePO 4 Battery Model Identification for Online SOC Estimation Application

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Optimal Sizing of Energy Storage Systems Using Frequency-Separation-Based Energy Management for Fuel Cell Hybrid Electric Vehicles

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Auto-Adaptive Filtering-Based Energy Management Strategy for Fuel Cell Hybrid Electric Vehicles

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Unknown input observer design for lithium-ion batteries SOC estimation based on a differential-algebraic model

International audienceAn accurate battery management strategy is a crucial need in the developing of reliable and viable plug in and hybrid electric vehicles. This on-board algorithm has the advantages to protect the battery from critical operating conditions and improve its lifetime. However, the effectiveness of the battery management strategy mainly depends on the accuracy of its state of charge (SOC). In this context, this paper proposes a novel technique for the SOC estimation based on the unknown input observer and a new differential-algebraic model of a lithium iron phosphate battery. The proposed observer aims to overcome the unknown value of the initial SOC for on-board batteries using only current and terminal voltage measurements. A reduced-order based unknown input observer is developed to estimate the open circuit voltage and the SOC using the OCV-SOC characteristic offlinedetermined. The unbiasedness of the estimation error is guaranteed by the parameterization of a set of Sylvester constraints. The performance of the proposed observer is verified by simulations and experiments and the accuracy of the obtained results is analyzed and assessed