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Sousso Kelouwani
Université du Québec à Trois-Rivières, 3351 Boulevard des Forges, Trois-Rivières, QC G8Z 4M3, Canada

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Short communication
Published: 26 August 2021 in Case Studies in Thermal Engineering
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The challenge of reducing vehicle energy consumption and greenhouse gas emissions has become a major orientation of automotive industry research throughout the world. Improving and optimizing power consumption by electric vehicles is of special concern. A novel use of thermoelectric generators in vehicle braking is presented. Thermal analysis of brake pads and discs using finite elements was applied to evaluate the energy potentially available in the form of heat produced by the friction involved in braking. We present stimulations of disc heating during and after braking at three ambient temperatures and reflect on the possibilities of energy recovery in warm as well as cold climates. The results show that although the yield of electrical energy from typical thermoelectric generators is about 0.3% of the total thermal energy associated with braking, at least 4 W can be made available, enough to power on-board instrumentation and vehicle devices and thereby improve the energy efficiency of motor vehicles.

ACS Style

Adama Coulibaly; Nadjet Zioui; Said Bentouba; Sousso Kelouwani; Mahmoud Bourouis. Use of thermoelectric generators to harvest energy from motor vehicle brake discs. Case Studies in Thermal Engineering 2021, 28, 101379 .

AMA Style

Adama Coulibaly, Nadjet Zioui, Said Bentouba, Sousso Kelouwani, Mahmoud Bourouis. Use of thermoelectric generators to harvest energy from motor vehicle brake discs. Case Studies in Thermal Engineering. 2021; 28 ():101379.

Chicago/Turabian Style

Adama Coulibaly; Nadjet Zioui; Said Bentouba; Sousso Kelouwani; Mahmoud Bourouis. 2021. "Use of thermoelectric generators to harvest energy from motor vehicle brake discs." Case Studies in Thermal Engineering 28, no. : 101379.

Review
Published: 13 June 2021 in Energies
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In recent years, the use of electric Autonomous Wheeled Mobile Robots (AWMRs) has dramatically increased in transport of the production chain. Generally, AWMRs must operate for several hours on a single battery charge. Since the energy density of the battery is limited, energy efficiency becomes a key element in improving material transportation performance during the manufacturing process. However, energy consumption is influenced by the navigation stages, because the type of motion necessary for the AWMR to perform during a mission is totally defined by these stages. Therefore, this paper analyzes methods of energy efficiency that have been studied recently for AWMR navigation stages. The selected publications are classified into planning and motion control categories in order to identify research gaps. Unlike other similar studies, this work focuses on these methods with respect to their implications for the energy consumption of AWMRs. In addition, by using an industrial Self-Guided Vehicle (SGV), we illustrate the direct influence of the motion planning stage on global energy consumption by means of several simulations and experiments. The results indicate that the reaction of the SGV in response to unforeseen obstacles can affect the amount of energy consumed. Hence, energy constraints must be considered when developing the motion planning of AWMRs.

ACS Style

Mohammad Mohammadpour; Lotfi Zeghmi; Sousso Kelouwani; Marc-André Gaudreau; Ali Amamou; Massinissa Graba. An Investigation into the Energy-Efficient Motion of Autonomous Wheeled Mobile Robots. Energies 2021, 14, 3517 .

AMA Style

Mohammad Mohammadpour, Lotfi Zeghmi, Sousso Kelouwani, Marc-André Gaudreau, Ali Amamou, Massinissa Graba. An Investigation into the Energy-Efficient Motion of Autonomous Wheeled Mobile Robots. Energies. 2021; 14 (12):3517.

Chicago/Turabian Style

Mohammad Mohammadpour; Lotfi Zeghmi; Sousso Kelouwani; Marc-André Gaudreau; Ali Amamou; Massinissa Graba. 2021. "An Investigation into the Energy-Efficient Motion of Autonomous Wheeled Mobile Robots." Energies 14, no. 12: 3517.

Journal article
Published: 03 March 2021 in IEEE Transactions on Energy Conversion
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Designing an accurate model for a proton exchange membrane fuel cell (PEMFC) is very difficult owing to its multivariate nature. Hence, PEMFC online system identification (OSI), which serves as a basis for its application in energy management of hybrid fuel cell vehicles, is considerably important to cope with the performance drifts. In this paper, an OSI method is proposed for estimating the time-varying parameters of a well-known PEMFC semi-empirical model in the literature. Unlike the other similar approaches, the proposed technique in this manuscript suggests a Lyapunov-based adaptation law with guaranteed stability to estimate online the fuel cell's parameters. To highlight the effectiveness of the suggested approach, it is used to estimate the characteristics of a 500-W Horizon PEMFC and its performance is compared with Kalman filter which is perceived as a reliable linear estimator. Experimental results along with the comparative study prove the successful performance of the suggested technique.

ACS Style

Mohsen Kandidayeni; Hicham Chaoui; Loic Boulon; Sousso Kelouwani; Joao Pedro Fernandes Trovao. Online System Identification of a Fuel Cell Stack with Guaranteed Stability for Energy Management Applications. IEEE Transactions on Energy Conversion 2021, PP, 1 -1.

AMA Style

Mohsen Kandidayeni, Hicham Chaoui, Loic Boulon, Sousso Kelouwani, Joao Pedro Fernandes Trovao. Online System Identification of a Fuel Cell Stack with Guaranteed Stability for Energy Management Applications. IEEE Transactions on Energy Conversion. 2021; PP (99):1-1.

Chicago/Turabian Style

Mohsen Kandidayeni; Hicham Chaoui; Loic Boulon; Sousso Kelouwani; Joao Pedro Fernandes Trovao. 2021. "Online System Identification of a Fuel Cell Stack with Guaranteed Stability for Energy Management Applications." IEEE Transactions on Energy Conversion PP, no. 99: 1-1.

Journal article
Published: 02 March 2021 in IEEE Access
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Due to the impact of human lifestyle on building energy consumption, the development of occupants’ behavior models is crucial for energy-saving purposes. In this regard, occupancy modeling is an effective approach to intend such a purpose. However, the literature reveals that existing occupancy models have limitations related to the representation of occupancy state duration and the integration of occupancy variability among individuals. Accordingly, this paper proposes an explicit differentiated duration probabilistic model to generate realistic daily occupancy profiles in residential buildings. The discrete-time Markov chain theory and the semi-parametric Cox proportional hazards model (Cox regression) are used to predict household occupancy profiles. The proposed model is able to capture occupancy states duration and integrate human behavior variability according to individuals’ characteristics. Moreover, a parametric analysis is employed to investigate these characteristics’ impact on the model performance and consequently, select the most significant input variables. A validation process is conducted by comparing the model performance with that of previous methods, presented in the literature. For this purpose, the $k$ cross-validation technique is utilized. Validation results demonstrate that the proposed approach is highly efficient in generating realistic household occupancy profiles.

ACS Style

Luis Rueda; Simon Sansregret; Brice Le Lostec; Kodjo Agbossou; Nilson Henao; Sousso Kelouwani. A Probabilistic Model to Predict Household Occupancy Profiles for Home Energy Management Applications. IEEE Access 2021, 9, 38187 -38201.

AMA Style

Luis Rueda, Simon Sansregret, Brice Le Lostec, Kodjo Agbossou, Nilson Henao, Sousso Kelouwani. A Probabilistic Model to Predict Household Occupancy Profiles for Home Energy Management Applications. IEEE Access. 2021; 9 ():38187-38201.

Chicago/Turabian Style

Luis Rueda; Simon Sansregret; Brice Le Lostec; Kodjo Agbossou; Nilson Henao; Sousso Kelouwani. 2021. "A Probabilistic Model to Predict Household Occupancy Profiles for Home Energy Management Applications." IEEE Access 9, no. : 38187-38201.

Review
Published: 24 February 2021 in IEEE Access
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High penetration of selfish Home Energy Management Systems (HEMSs) causes adverse effects such as rebound peaks, instabilities, and contingencies in different regions of distribution grid. To avoid these effects and relieve power grid stress, the concept of HEMSs coordination has been suggested. Particularly, this concept can be employed to fulfill important grid objectives in neighborhood areas such as flattening aggregated load profile, decreasing electricity bills, facilitating energy trading, diminishing reverse power flow, managing distributed energy resources, and modifying consumers' consumption/generation patterns. This paper reviews the latest investigations into coordinated HEMSs. The required steps to implement these systems, accounting for coordination topologies and techniques, are thoroughly explored. This exploration is mainly reported through classifying coordination approaches according to their utilization of decomposition algorithms. Furthermore, major features, advantages, and disadvantages of the methods are examined. Specifically, coordination process characteristics, its mathematical issues and essential prerequisites, as well as players concerns are analyzed. Subsequently, specific applications of coordination designs are discussed and categorized. Through a comprehensive investigation, this work elaborates significant remarks on critical gaps in existing studies toward a useful coordination structure for practical HEMSs implementations. Unlike other reviews, the present survey focuses on effective frameworks to determine future opportunities that make the concept of coordinated HEMSs feasible. Indeed, providing effective studies on HEMSs coordination concept is beneficial to both consumers and service providers since as reported, these systems can lead to 5% to 30% reduction in electricity bills.

ACS Style

Farshad Etedadi Aliabadi; Kodjo Agbossou; Sousso Kelouwani; Nilson Henao; Sayed Saeed Hosseini. Coordination of Smart Home Energy Management Systems in Neighborhood Areas: A Systematic Review. IEEE Access 2021, 9, 36417 -36443.

AMA Style

Farshad Etedadi Aliabadi, Kodjo Agbossou, Sousso Kelouwani, Nilson Henao, Sayed Saeed Hosseini. Coordination of Smart Home Energy Management Systems in Neighborhood Areas: A Systematic Review. IEEE Access. 2021; 9 ():36417-36443.

Chicago/Turabian Style

Farshad Etedadi Aliabadi; Kodjo Agbossou; Sousso Kelouwani; Nilson Henao; Sayed Saeed Hosseini. 2021. "Coordination of Smart Home Energy Management Systems in Neighborhood Areas: A Systematic Review." IEEE Access 9, no. : 36417-36443.

Journal article
Published: 11 December 2020 in IEEE Transactions on Power Electronics
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This paper presents a real-time parameter estimation of a proton exchange membrane fuel cell (PEMFC). The proposed strategy estimates online the PEMFC's resistance since it is directly correlated to its remaining useful life (RUL) assessment. The estimation of the PEMFC's parameters is a difficult task to undertake due to various uncertainties, like temperature and aging, that lead to a drift in parameters and limit the performance of the overall energy system. Therefore, online system identification is essential to track online the PEMFC's time-varying parameters. Unlike other identification techniques, the proposed strategy is based on a simple yet accurate PEMFC's model and adjusts its parameters in real-time using a Lyapunov-based adaptation law, which yields guaranteed stability. Experiments are conducted on a 500-W Horizon PEMFC and results along with a comparison against the well-known Kalman filter highlight the effectiveness of the proposed approach which is instrumental for its numerous applications, such as the energy management of hybrid fuel cell vehicles.

ACS Style

Hicham Chaoui; Mohsen Kandidayeni; Loic Boulon; Sousso Kelouwani; Hamid Gualous. Real-Time Parameter Estimation of a Fuel Cell for Remaining Useful Life Assessment. IEEE Transactions on Power Electronics 2020, 36, 7470 -7479.

AMA Style

Hicham Chaoui, Mohsen Kandidayeni, Loic Boulon, Sousso Kelouwani, Hamid Gualous. Real-Time Parameter Estimation of a Fuel Cell for Remaining Useful Life Assessment. IEEE Transactions on Power Electronics. 2020; 36 (7):7470-7479.

Chicago/Turabian Style

Hicham Chaoui; Mohsen Kandidayeni; Loic Boulon; Sousso Kelouwani; Hamid Gualous. 2020. "Real-Time Parameter Estimation of a Fuel Cell for Remaining Useful Life Assessment." IEEE Transactions on Power Electronics 36, no. 7: 7470-7479.

Review
Published: 15 November 2020 in Sensors
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Perception is a vital part of driving. Every year, the loss in visibility due to snow, fog, and rain causes serious accidents worldwide. Therefore, it is important to be aware of the impact of weather conditions on perception performance while driving on highways and urban traffic in all weather conditions. The goal of this paper is to provide a survey of sensing technologies used to detect the surrounding environment and obstacles during driving maneuvers in different weather conditions. Firstly, some important historical milestones are presented. Secondly, the state-of-the-art automated driving applications (adaptive cruise control, pedestrian collision avoidance, etc.) are introduced with a focus on all-weather activity. Thirdly, the most involved sensor technologies (radar, lidar, ultrasonic, camera, and far-infrared) employed by automated driving applications are studied. Furthermore, the difference between the current and expected states of performance is determined by the use of spider charts. As a result, a fusion perspective is proposed that can fill gaps and increase the robustness of the perception system.

ACS Style

Abdul Sajeed Mohammed; Ali Amamou; Follivi Kloutse Ayevide; Sousso Kelouwani; Kodjo Agbossou; Nadjet Zioui. The Perception System of Intelligent Ground Vehicles in All Weather Conditions: A Systematic Literature Review. Sensors 2020, 20, 6532 .

AMA Style

Abdul Sajeed Mohammed, Ali Amamou, Follivi Kloutse Ayevide, Sousso Kelouwani, Kodjo Agbossou, Nadjet Zioui. The Perception System of Intelligent Ground Vehicles in All Weather Conditions: A Systematic Literature Review. Sensors. 2020; 20 (22):6532.

Chicago/Turabian Style

Abdul Sajeed Mohammed; Ali Amamou; Follivi Kloutse Ayevide; Sousso Kelouwani; Kodjo Agbossou; Nadjet Zioui. 2020. "The Perception System of Intelligent Ground Vehicles in All Weather Conditions: A Systematic Literature Review." Sensors 20, no. 22: 6532.

Review
Published: 15 October 2020 in Sustainability
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Automated industrial vehicles are taking an imposing place by transforming the industrial operations, and contributing to an efficient in-house transportation of goods. They are expected to bring a variety of benefits towards the Industry 4.0 transition. However, Self-Guided Vehicles (SGVs) are battery-powered, unmanned autonomous vehicles. While the operating durability depends on self-path design, planning energy-efficient paths become crucial. Thus, this paper has no concrete contribution but highlights the lack of energy consideration of SGV-system design in literature by presenting a review of energy-constrained global path planning. Then, an experimental investigation explores the long-term effect of battery level on navigation performance of a single vehicle. This experiment was conducted for several hours, a deviation between the global trajectory and the ground-true path executed by the SGV was observed as the battery depleted. The results show that the mean square error (MSE) increases significantly as the battery’s state-of-charge decreases below a certain value.

ACS Style

Massinissa Graba; Sousso Kelouwani; Lotfi Zeghmi; Ali Amamou; Kodjo Agbossou; Mohammad Mohammadpour. Investigating the Impact of Energy Source Level on the Self-Guided Vehicle System Performances, in the Industry 4.0 Context. Sustainability 2020, 12, 8541 .

AMA Style

Massinissa Graba, Sousso Kelouwani, Lotfi Zeghmi, Ali Amamou, Kodjo Agbossou, Mohammad Mohammadpour. Investigating the Impact of Energy Source Level on the Self-Guided Vehicle System Performances, in the Industry 4.0 Context. Sustainability. 2020; 12 (20):8541.

Chicago/Turabian Style

Massinissa Graba; Sousso Kelouwani; Lotfi Zeghmi; Ali Amamou; Kodjo Agbossou; Mohammad Mohammadpour. 2020. "Investigating the Impact of Energy Source Level on the Self-Guided Vehicle System Performances, in the Industry 4.0 Context." Sustainability 12, no. 20: 8541.

Journal article
Published: 24 September 2020 in Energies
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This paper deals with the design of an energy management strategy (EMS) for an industrial hybrid self-guided vehicle (SGV), considering the size of a fuel cell (FC) stack and degradation of a battery pack. In this context, first, a realistic energy model of the SGV was proposed and validated, based on experiments. This model provided a basis for individual components analysis, estimating energy requirements, component sizing, and testing various EMSs, prior to practical implementation. Second, the performance of the developed FC/battery SGV powertrain was validated under three EMS modes. Each mode was studied by considering four different FC sizes and three battery degradation levels. The final results showed that a small FC as a range extender is recommended, to reduce system cost. It is also important to maintain the FC in its high efficiency zones with a minimum ON/OFF cycle, leading to efficiency and lifetime enhancement of FC system. Battery SOC have to be kept at a high level during SGV operation, to support the FC during SGV acceleration. In order to improve the SGV’s overall autonomy, it is also important to minimize the stop and go and rotational SGV motion with appropriate acceleration and deceleration rate.

ACS Style

Amin Ghobadpour; Ali Amamou; Sousso Kelouwani; Nadjet Zioui; Lotfi Zeghmi. Impact of Powertrain Components Size and Degradation Level on the Energy Management of a Hybrid Industrial Self-Guided Vehicle. Energies 2020, 13, 5041 .

AMA Style

Amin Ghobadpour, Ali Amamou, Sousso Kelouwani, Nadjet Zioui, Lotfi Zeghmi. Impact of Powertrain Components Size and Degradation Level on the Energy Management of a Hybrid Industrial Self-Guided Vehicle. Energies. 2020; 13 (19):5041.

Chicago/Turabian Style

Amin Ghobadpour; Ali Amamou; Sousso Kelouwani; Nadjet Zioui; Lotfi Zeghmi. 2020. "Impact of Powertrain Components Size and Degradation Level on the Energy Management of a Hybrid Industrial Self-Guided Vehicle." Energies 13, no. 19: 5041.

Journal article
Published: 07 September 2020 in Energies
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The use of a direct torque control (DTC) drive is a well-known control strategy that is applied frequently to induction motors. Although torque and stator flux ripples are major disadvantages of this approach, using a higher-level inverter helps to overcome these issues. In this paper, we propose a novel switching table with a modified control strategy for a three-level inverter to achieve ripple minimization, as well as smooth switching and neutral point balance; the latter features are generally ignored in many works. The proposed model is compared with a conventional DTC and an improved three-level inverter-fed voltage vector synthesis model in the Matlab/Simulink® environment with low, normal, and high-speed operation under load torque disturbances. The performance indexes and the comparative results confirm the effectiveness of the proposed model in reducing the torque and stator flux ripples by up to 70% and 78%, respectively, generating a lower total harmonic distortion (THD%) in all scenarios, in addition to maintaining the neutral point balance and preventing voltage jumps across the switches of the inverter.

ACS Style

Yashar Farajpour; Mohamad Alzayed; Hicham Chaoui; Sousso Kelouwani. A Novel Switching Table for a Modified Three-Level Inverter-Fed DTC Drive with Torque and Flux Ripple Minimization. Energies 2020, 13, 4646 .

AMA Style

Yashar Farajpour, Mohamad Alzayed, Hicham Chaoui, Sousso Kelouwani. A Novel Switching Table for a Modified Three-Level Inverter-Fed DTC Drive with Torque and Flux Ripple Minimization. Energies. 2020; 13 (18):4646.

Chicago/Turabian Style

Yashar Farajpour; Mohamad Alzayed; Hicham Chaoui; Sousso Kelouwani. 2020. "A Novel Switching Table for a Modified Three-Level Inverter-Fed DTC Drive with Torque and Flux Ripple Minimization." Energies 13, no. 18: 4646.

Journal article
Published: 23 July 2020 in IEEE Transactions on Vehicular Technology
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This paper puts forward an adaptive cold start strategy for a proton exchange membrane fuel cell (PEMFC) based on maximum power mode. The proposed strategy consists of a water evacuation process after PEMFC shutdown and a self-heating process at PEMFC cold startup. To maximize the performance of the suggested strategy, an optimal operating condition for the cold start procedure is sought first. In this respect, an experimental parametric study is performed to explore the impact of fan velocity, micro-short circuit, anode pressure, and purge procedure on the PEMFC cold start performance. After laying down the proper conditions, the proposed cold start procedure is implemented on a test bench for experimental validations. The self-heating process is based on an online adaptive algorithm that maximizes the PEMFCs internal heat depending on its operating parameters variation. In fact, this algorithm attempts to keep the current density at high levels, leading to PEMFCs performance improvement achieved by membrane hydration and temperature increase. The experimental results confirm the effectiveness of the proposed strategy, which presents a fast and cost-effective PEMFCs cold start.

ACS Style

Ali Akram Amamou; Mohsen Kandidayeni; Sousso Kelouwani; Loic Boulon. An Online Self Cold Startup Methodology for PEM Fuel Cells in Vehicular Applications. IEEE Transactions on Vehicular Technology 2020, 69, 14160 -14172.

AMA Style

Ali Akram Amamou, Mohsen Kandidayeni, Sousso Kelouwani, Loic Boulon. An Online Self Cold Startup Methodology for PEM Fuel Cells in Vehicular Applications. IEEE Transactions on Vehicular Technology. 2020; 69 (12):14160-14172.

Chicago/Turabian Style

Ali Akram Amamou; Mohsen Kandidayeni; Sousso Kelouwani; Loic Boulon. 2020. "An Online Self Cold Startup Methodology for PEM Fuel Cells in Vehicular Applications." IEEE Transactions on Vehicular Technology 69, no. 12: 14160-14172.

Journal article
Published: 29 June 2020 in International Journal of Hydrogen Energy
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The PEMFC maximum power is greatly influenced by subfreezing temperature and degradation phenomena. Therefore, a dependable model is required to estimate the power with respect to the variation of the operating conditions and state of health. Semi-empirical models are potent tools in this regard. Nonetheless, there is not much information about their cold environment reliability. This paper comprehensively compares the performance of some models (already tested in normal ambient temperature) in subfreezing condition to introduce the most reliable one for PEMFC cold start-up application. Firstly, seven models are compared regarding voltage losses and precision. Subsequently, the three most dependable ones are selected and experimentally compared at sub-zero temperature in terms of polarization curve estimation for three PEMFCs with different degradation levels. The results of this study indicate that the model introduced by Amphlett et al. has a superior performance compared to other ones regarding the characteristic's estimation in below-zero temperature.

ACS Style

A. Amamou; M. Kandidayeni; A. Macias; L. Boulon; S. Kelouwani. Efficient model selection for real-time adaptive cold start strategy of a fuel cell system on vehicular applications. International Journal of Hydrogen Energy 2020, 45, 19664 -19675.

AMA Style

A. Amamou, M. Kandidayeni, A. Macias, L. Boulon, S. Kelouwani. Efficient model selection for real-time adaptive cold start strategy of a fuel cell system on vehicular applications. International Journal of Hydrogen Energy. 2020; 45 (38):19664-19675.

Chicago/Turabian Style

A. Amamou; M. Kandidayeni; A. Macias; L. Boulon; S. Kelouwani. 2020. "Efficient model selection for real-time adaptive cold start strategy of a fuel cell system on vehicular applications." International Journal of Hydrogen Energy 45, no. 38: 19664-19675.

Review
Published: 12 June 2020 in Building and Environment
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Detailed occupancy information in buildings is useful to improve the performance of energy management systems in order to enable energy consumption savings and maintain occupants' comfort. Different technologies employed to provide occupancy information account for high-precision devices such as optical and thermal cameras, and environmental or specialized sensors like carbon dioxide (CO2) and passive infrared (PIR). Although the latter systems have lower accuracy, they have received significant interest due to their affordable and less-intrusive nature. Accordingly, various studies have been conducted to explore the various elements of these technologies. Nevertheless, the algorithmic aspect of the occupancy detection process has not been adequately taken into consideration. This paper presents an extensive review of the techniques that have been exploited to process the information provided by the sensors and carry out occupancy information detection. In this study, a complete set of comparison criteria, comprising the performance, the occupancy resolution, the type of sensors used, the type of buildings, and the energy saving potentials has been considered in order to perform an in-depth analysis of the occupancy detection systems. Through its examination, this paper elaborates significant remarks on occupancy detection algorithms in order to realize a method that is not only efficient in processing sensors’ data but also effective in providing accurate occupancy information.

ACS Style

Luis Rueda; Kodjo Agbossou; Alben Cardenas; Nilson Henao; Sousso Kelouwani. A comprehensive review of approaches to building occupancy detection. Building and Environment 2020, 180, 106966 .

AMA Style

Luis Rueda, Kodjo Agbossou, Alben Cardenas, Nilson Henao, Sousso Kelouwani. A comprehensive review of approaches to building occupancy detection. Building and Environment. 2020; 180 ():106966.

Chicago/Turabian Style

Luis Rueda; Kodjo Agbossou; Alben Cardenas; Nilson Henao; Sousso Kelouwani. 2020. "A comprehensive review of approaches to building occupancy detection." Building and Environment 180, no. : 106966.

Journal article
Published: 12 May 2020 in IEEE Transactions on Industrial Electronics
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ACS Style

Mohsen Kandidayeni; Alvaro Macias; Loic Boulon; Sousso Kelouwani. Efficiency Upgrade of Hybrid Fuel Cell Vehicles’ Energy Management Strategies by Online Systemic Management of Fuel Cell. IEEE Transactions on Industrial Electronics 2020, 68, 4941 -4953.

AMA Style

Mohsen Kandidayeni, Alvaro Macias, Loic Boulon, Sousso Kelouwani. Efficiency Upgrade of Hybrid Fuel Cell Vehicles’ Energy Management Strategies by Online Systemic Management of Fuel Cell. IEEE Transactions on Industrial Electronics. 2020; 68 (6):4941-4953.

Chicago/Turabian Style

Mohsen Kandidayeni; Alvaro Macias; Loic Boulon; Sousso Kelouwani. 2020. "Efficiency Upgrade of Hybrid Fuel Cell Vehicles’ Energy Management Strategies by Online Systemic Management of Fuel Cell." IEEE Transactions on Industrial Electronics 68, no. 6: 4941-4953.

Journal article
Published: 04 May 2020 in Energies
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An efficient participation of prosumers in power system management depends on the quality of information they can obtain. Prosumers actions can be performed by automated agents that are operating in time-changing environments. Therefore, it is essential for them to deal with data stream problems in order to make reliable decisions based on the most accurate information. This paper provides an in-depth investigation of data and concept drift issues in accordance with residential prosumer agents. Additionally, the adaptation techniques, forgetting mechanisms, and learning strategies employed to handle these issues are explored. Accordingly, an approach is proposed to adapt the prosumer agent models to overcome the gradual and sudden concept drift concurrently. The suggested method is based on triggered adaptation techniques and performance-based forgetting mechanism. The results obtained in this study demonstrate that the proposed approach is capable of constructing efficient prosumer agents models with regard to the concept drift problem.

ACS Style

David Toquica; Kodjo Agbossou; Roland Malhamé; Nilson Henao; Sousso Kelouwani; David Camilo Toquica Cárdenas. Adaptive Machine Learning for Automated Modeling of Residential Prosumer Agents. Energies 2020, 13, 2250 .

AMA Style

David Toquica, Kodjo Agbossou, Roland Malhamé, Nilson Henao, Sousso Kelouwani, David Camilo Toquica Cárdenas. Adaptive Machine Learning for Automated Modeling of Residential Prosumer Agents. Energies. 2020; 13 (9):2250.

Chicago/Turabian Style

David Toquica; Kodjo Agbossou; Roland Malhamé; Nilson Henao; Sousso Kelouwani; David Camilo Toquica Cárdenas. 2020. "Adaptive Machine Learning for Automated Modeling of Residential Prosumer Agents." Energies 13, no. 9: 2250.

Journal article
Published: 01 October 2019 in IEEE Transactions on Vehicular Technology
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This paper addresses the design of a systemic management to improve the energetic efficiency of an open cathode proton exchange membrane fuel cell (PEMFC) in a hybrid system. Unlike the other similar works, the proposed approach capitalizes on the usage of both thermal management strategy and current control to meet the requested power from the system by the minimum fuel consumption. To do so, firstly, an experimentally based 3D mapping is performed to relate the requested power form the PEMFC to its operating temperature and current. Secondly, the reference temperature which leads to gaining the demanded power by the minimum current level is determined to minimize the hydrogen consumption. Finally, the temperature control is formulated by an optimized fuzzy logic scheme to reach the determined reference temperature by acting on the cooling fan of the PEMFC system, whilst the current is being regulated by its controller. The inputs of the fuzzy controller are the PEMFC current and temperature error and the sole output is the duty factor of the fan. The proposed methodology is tested on an experimental test bench to be better evaluated in a real condition. The obtained results from the proposed systemic management indicate promising enhancement of the system efficiency compared to a commercial controller. The proposed method of this work is extendable and applicable in fuel cell hybrid electric vehicles.

ACS Style

Mohsen Kandidayeni; Alvaro Macias F.; Loic Boulon; Sousso Kelouwani. Efficiency Enhancement of an Open Cathode Fuel Cell Through a Systemic Management. IEEE Transactions on Vehicular Technology 2019, 68, 11462 -11472.

AMA Style

Mohsen Kandidayeni, Alvaro Macias F., Loic Boulon, Sousso Kelouwani. Efficiency Enhancement of an Open Cathode Fuel Cell Through a Systemic Management. IEEE Transactions on Vehicular Technology. 2019; 68 (12):11462-11472.

Chicago/Turabian Style

Mohsen Kandidayeni; Alvaro Macias F.; Loic Boulon; Sousso Kelouwani. 2019. "Efficiency Enhancement of an Open Cathode Fuel Cell Through a Systemic Management." IEEE Transactions on Vehicular Technology 68, no. 12: 11462-11472.

Journal article
Published: 21 August 2019 in IEEE Transactions on Vehicular Technology
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Energy management strategy (EMS) has a profound influence over the performance of a fuel cell hybrid electric vehicle since it can maintain the energy sources in their high efficacy zones leading to efficiency and lifetime enhancement of the system. This paper puts forward an online multi-mode EMS to efficiently split the power among the components while embracing the effects of the driving conditions and performance degradation of the fuel cell system. In this regard, firstly, a self-organizing map (SOM) is trained to cluster the driving patterns. The SOM competitive layer in this work is composed of ten driving features as inputs and it classifies the driving patterns into three classes in the output. Subsequently, a three-mode fuzzy logic controller (FLC) is designed and optimized offline by the genetic algorithm for each driving pattern. Unlike the other similar works, the output membership function of the FLC is designed based on the online identification of the maximum power and efficiency of the fuel cell system which change over time. Finally, the SOM is utilized to recognize the driving mode at each sequence and accordingly activate the most suitable mode of the FLC to meet the requested power by efficient use of the energy sources. The performance of the proposed EMS has been validated by using the hardware-in-the-loop platform for several scenarios. The experimental results analyses indicate the promising performance of the suggested methodology in terms of ameliorating hydrogen economy and the fuel cell system lifetime.

ACS Style

Mohsen Kandidayeni; Alvaro Omar Macias Fernandez; Arash Khalatbarisoltani; Loic Boulon; Sousso Kelouwani; Hicham Chaoui. An Online Energy Management Strategy for a Fuel Cell/Battery Vehicle Considering the Driving Pattern and Performance Drift Impacts. IEEE Transactions on Vehicular Technology 2019, 68, 11427 -11438.

AMA Style

Mohsen Kandidayeni, Alvaro Omar Macias Fernandez, Arash Khalatbarisoltani, Loic Boulon, Sousso Kelouwani, Hicham Chaoui. An Online Energy Management Strategy for a Fuel Cell/Battery Vehicle Considering the Driving Pattern and Performance Drift Impacts. IEEE Transactions on Vehicular Technology. 2019; 68 (12):11427-11438.

Chicago/Turabian Style

Mohsen Kandidayeni; Alvaro Omar Macias Fernandez; Arash Khalatbarisoltani; Loic Boulon; Sousso Kelouwani; Hicham Chaoui. 2019. "An Online Energy Management Strategy for a Fuel Cell/Battery Vehicle Considering the Driving Pattern and Performance Drift Impacts." IEEE Transactions on Vehicular Technology 68, no. 12: 11427-11438.

Journal article
Published: 02 May 2019 in International Journal of Electrical Power & Energy Systems
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Enabling diagnosis capabilities of Appliance Load Monitoring (ALM) necessitates providing in-operation information of appliances’ behavior. Due to both appliances’ time-varying model parameters and operations, household aggregated consumption has a dynamic structure. Existing time-invariant load models, built of off-line datasets with static information, are not sufficient to capture the actual behavior of the power consumption. In fact, these models, generally obtained from exhaustive training phases are intended to satisfy load monitoring goals. Therefore, a time-variant load modeling is more practical to capture such a dynamic property of the power consumption. Accordingly, this paper presents an adaptive on-line appliance-level load modeling approach, to design a load monitoring structure for diagnosis purposes. By using the aggregated power consumption of individual households, our proposed structure results in an autonomous household database construction. The modeling procedure begins with a designed recurrent pattern recognition system that is capable of detecting and maintaining load models. This load model structure is determined by using a hidden Markov model (HMM) with dynamic parameters, that are extracted from aggregated signal and trained within an on-line learning process. Our proposed approach can detect time-varying power consumption behavior and estimate the robust load models of appliances. Additionally, our novelty in employing a set of straightforward algorithms, suggests the practicality of our database construction approach.

ACS Style

Sayed Saeed Hosseini; Sousso Kelouwani; Kodjo Agbossou; Alben Cardenas; Nilson Henao. Adaptive on-line unsupervised appliance modeling for autonomous household database construction. International Journal of Electrical Power & Energy Systems 2019, 112, 156 -168.

AMA Style

Sayed Saeed Hosseini, Sousso Kelouwani, Kodjo Agbossou, Alben Cardenas, Nilson Henao. Adaptive on-line unsupervised appliance modeling for autonomous household database construction. International Journal of Electrical Power & Energy Systems. 2019; 112 ():156-168.

Chicago/Turabian Style

Sayed Saeed Hosseini; Sousso Kelouwani; Kodjo Agbossou; Alben Cardenas; Nilson Henao. 2019. "Adaptive on-line unsupervised appliance modeling for autonomous household database construction." International Journal of Electrical Power & Energy Systems 112, no. : 156-168.

Journal article
Published: 04 February 2019 in IEEE Transactions on Sustainable Energy
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Previous studies have shown that electric water heaters (EWH) have strong potential in demand-side management applications, more precisely because they offer energy storage capability and then can be employed as shift loads. However, the challenge of EWH curtailment strategies is to minimize the impact on the hot water availability while shaving the peak of consumption during critical periods. The success of such strategies depends highly on the knowledge of the consumption behavior of each user. Thus, appropriated modeling and consumption analysis could yield better management strategies. This study proposes an electric water heater control strategy based on dynamic programming and power consumption profile classification. An adaptive clustering process allows recognizing the clients who contribute to the highest power consumption during the peak periods. The analysis and simulation indicate that an appropriate control on the group of users could be implemented to reduce peak demand and to meet the hot water demand. A K-means clustering algorithm has been used for cluster analysis. The silhouette method has been applied to estimate the appropriate number of clusters.

ACS Style

Maria Alejandra Zuniga Alvarez; Kodjo Agbossou; Alben Cardenas; Sousso Kelouwani; Loic Boulon. Demand Response Strategy Applied to Residential Electric Water Heaters Using Dynamic Programming and K-Means Clustering. IEEE Transactions on Sustainable Energy 2019, 11, 524 -533.

AMA Style

Maria Alejandra Zuniga Alvarez, Kodjo Agbossou, Alben Cardenas, Sousso Kelouwani, Loic Boulon. Demand Response Strategy Applied to Residential Electric Water Heaters Using Dynamic Programming and K-Means Clustering. IEEE Transactions on Sustainable Energy. 2019; 11 (1):524-533.

Chicago/Turabian Style

Maria Alejandra Zuniga Alvarez; Kodjo Agbossou; Alben Cardenas; Sousso Kelouwani; Loic Boulon. 2019. "Demand Response Strategy Applied to Residential Electric Water Heaters Using Dynamic Programming and K-Means Clustering." IEEE Transactions on Sustainable Energy 11, no. 1: 524-533.

Journal article
Published: 15 August 2018 in IEEE Transactions on Vehicular Technology
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This paper presents a bifuel hydrogen–gasoline internal combustion engine (ICE) as an effective strategy for extending the electric vehicle's ranges. The electric power produced by the proposed ICE linked with a generator is a nonlinear function of the engine speed and the proportions of hydrogen and gasoline mixed fuel can be approximated around operating conditions. This nonlinear function is approximated by the Taylor series and a comparative study between the obtained results and the experimental data showed the effectiveness of the proposed approach. Furthermore, we observed that the Taylor series approach can achieve less than 7% error, while the modeling with an artificial neural network or a recursive least square method results in more than 8% error. To enable the ICE operation with maximum efficiency, a nonlinear optimization method is used. The proposed maximum efficiency tracking approach is compared with that of the most used industrial methods based on constant speed. The results show that the proposed approach can result in more than 7% of saving in energy, compared to that of the industrial method.

ACS Style

Mohamed Rebai; Sousso Kelouwani; Yves Dube; Kodjo Agbossou. Low-Emission Maximum-Efficiency Tracking of an Intelligent Bi-Fuel Hydrogen–Gasoline Generator for HEV Applications. IEEE Transactions on Vehicular Technology 2018, 67, 9303 -9311.

AMA Style

Mohamed Rebai, Sousso Kelouwani, Yves Dube, Kodjo Agbossou. Low-Emission Maximum-Efficiency Tracking of an Intelligent Bi-Fuel Hydrogen–Gasoline Generator for HEV Applications. IEEE Transactions on Vehicular Technology. 2018; 67 (10):9303-9311.

Chicago/Turabian Style

Mohamed Rebai; Sousso Kelouwani; Yves Dube; Kodjo Agbossou. 2018. "Low-Emission Maximum-Efficiency Tracking of an Intelligent Bi-Fuel Hydrogen–Gasoline Generator for HEV Applications." IEEE Transactions on Vehicular Technology 67, no. 10: 9303-9311.