Nassim Rizoug

Modeling and Characterizing Supercapacitors Using an Online Method

In this paper, different modeling approaches representing the behavior of supercapacitors are presented. A hybrid modeling approach is developed to improve the characterization of classical supercapacitor models proposed in the literature. This approach uses various representations (frequency and temporal results) of the same cycling test to extract easily and with a good precision the parameters of the models. Then, it is applied for studying the ageing of this component, which mainly depends on the temperature and cycling process.

A Control Reconfiguration Strategy for Post-Sensor FTC in Induction Motor-Based EVs

This paper deals with experimental validation of a reconfiguration strategy for sensor fault-tolerant control (FTC) in induction-motor-based electric vehicles (EVs). The proposed active FTC system is illustrated using two control techniques: indirect field-oriented control (IFOC) in the case of healthy sensors and speed control with slip regulation (SCSR) in the case of failed current sensors. The main objective behind the reconfiguration strategy is to achieve a short and smooth transition when switching from a controller using a healthy sensor to another sensorless controller in the case of a sensor failure. The proposed FTC approach performances are experimentally evaluated on a 7.5-kW induction motor drive.

Li-Ion Battery Emulator for Electric Vehicle Applications

The Lithium-ion batteries are becoming increasingly used like an energy storage system for electric vehicles. This kind of batteries exhibits many advantages such as high energy density, no memory effect, high operation voltage, etc. . . On the other hand, the cost of this battery is higher compared to the other technologies and needs a good management using a battery management system (BMS). For that, the emulation of this component can decrease the development cost. In this paper a particular battery emulator based on power electronics device with an improved battery model will be presented. The developed system allows user to test the electrical vehicle at various battery behavior or ambient conditions. The advantage of this system is their ability to vary the internal parameters of the battery and also the creation of a default safely. The experimental results obtained with a dSPACE 1104 controller board show a well performance of the battery emulator and confirm the feasibility of our system.

Adaptive neural network control based on neural observer for quadrotor unmanned aerial vehicle

This paper proposes an adaptive neural network control with neural state’s observer for quadrotor. The adaptive approach is used to solve the dynamics uncertainty problem of the controller. To perform the control, a Single Hidden Layer Neural Network (SHLNN) is used. Based on the structure of Sliding Mode Observer (SMO), a new neural observer is proposed to estimate the states. The aim of this work is to propose an observer insensitive to the measurement noise. The stability proof of global system is made by Lyapunov direct method. The adaptation laws of both artificial neural networks (ANNs) are derived from Lyapunov theory. The proposed controller is validated by simulation on the quadrotor under measurement noise conditions. A comparative study with SMO is made to highlight the performances of the proposed neural observer. Graphical Abstract

Combined Optimal Sizing and Control of Li-Ion Battery/Supercapacitor Embedded Power Supply Using Hybrid Particle Swarm–Nelder–Mead Algorithm

This paper examines and optimizes parameters that affect the sizing and control of a hybrid embedded power supply composed of Li-ion batteries and supercapacitors in electric vehicle applications. High demands including power and energy density, low charge/discharge power stress on the battery (long lifetime), lightweight design, and relatively modest cost at the same time cannot be provided solely by batteries or supercapacitors. For this reason, we propose the use of a Li-ion battery/supercapacitor hybrid embedded power supply for an urban electric vehicle. The sizing process of this system including the optimization of the power sharing is done thanks to a developed hybrid Particle Swarm-Nelder-Mead algorithm involving multi-objective optimization. This approach also allows us to optimize the proposed energy management strategies based on frequency rule-based control and different ways of supercapacitors energy regulation. Obtained results show that the hybrid embedded power supply with the proposed control strategies is able to offer the best performances for the chosen electric vehicle in terms of weight, initial cost, and battery lifetime.

Observer-based Adaptive Fuzzy Backstepping Tracking Control of Quadrotor Unmanned Aerial Vehicle Powered by Li-ion Battery

In this paper, an Adaptive Fuzzy Backstepping Control (AFBC) approach with state observer is developed. This approach is used to overcome the problem of trajectory tracking for a Quadrotor Unmanned Aerial Vehicle (QUAV) under wind gust conditions and parametric uncertainties. An adaptive fuzzy controller is directly used to approximate an unknown nonlinear backstepping controller which is based on the exact model of the QUAV. Besides, a state observer is constructed to estimate the states. The stability analysis of the whole system is proved using Lyapunov direct method. Uniformly Ultimately Bounded (UUB) stability of all signals in the closed-loop system is ensured. The proposed control method guarantees the tracking of a desired trajectory, attenuates the effect of external disturbances such as wind gust, and solves the problem of unavailable states for measurement. Extended simulation studies are presented to highlight the efficiency of the proposed AFBC scheme.

Influence of the management strategies on the sizing of hybrid supply composed with battery and supercapacitor

The use of hybrid sources in the field of electronic vehicles becomes very interesting solution to reduce the weight of the source. The asked question using this kind of sources is how we should manage the power and the energy between the two hybrid components in order to ensure an optimal sizing of the source in terms of weight, volume, autonomy, and aging?. This article presents the sizing of hybrids sources composed with battery and supercapacitor packs. In this study, two management strategies are tested: limitation of power strategy, and filtering strategy. The obtained results with the two strategies will be compared in order to know which strategy allows to reduce the size of the source.

Sizing and Energy Management Strategy for hybrid FC/Battery electric vehicle

This paper focalizes on sizing of hybrids sources composed with Fuel cells FCs and battery pack. Also an experimental validation of energy management of FC/Battery electric vehicle is tested. The system is composed of a fuel cell system as the main source and batteries as an assisting one. This last one is connected to a bidirectional DC/DC converter, and a DC/DC boost converter is associated to the fuel cell stack. To increase the power efficiency and to achieve the best performances of the hybrid source, an online EM strategy is used to share the power between the main and the auxiliary source by determining the power profile of each one. This strategy is based on frequency separation; it takes into account the slow dynamics of FC, fuel consumption and the batteries limits. Also, it is needed to make these results as a reference to be compared with other strategies which are currently under development in our laboratory. In the objective to verify the efficiency of the proposed approach, both simulation and experimental results leads to confirm its efficiency, the robustness and stability regrading dynamic performances during power demand, and regenerative braking, fuel consumption.

Optimal Energy Management for a Li-Ion Battery/Supercapacitor Hybrid Energy Storage System Based on a Particle Swarm Optimization Incorporating Nelder–Mead Simplex Approach

Combining a high-power source like a supercapacitor with a lithium-ion battery for electric vehicle applications results in performance improvements, high efficiency, long lifetime, lightweight design, and relatively modest cost of the overall source. A hybrid energy storage system controlled by a smart energy management strategy can play a key role in the design and development of multisource electric vehicles. In this study, an optimal energy management strategy based on particle swarm optimization incorporating the Nelder–Mead simplex method is proposed. The goal of the proposed strategy is to minimize the battery power stress and improve its lifetime. This is achieved by coupling a rule-based method based on the knowledge of the battery and supercapacitor efficiency operating with a hybrid Particle Swarm–Nelder–Mead optimization algorithm. This latter approach is proposed to optimize the control parameters of the rule-based energy management strategy. Once the offline optimization algorithm is completed, the control method can be implemented online. The developed strategy is tested in a simulation environment and in an experimental platform using a power emulator test bench of a lithium-ion battery/supercapacitor hybrid energy storage system. The results, in terms of battery power stress and lifetime, are compared with a conventional rule-based method and a monosource with a single high-power lithium-ion battery. Obtained results show the effectiveness of the proposed strategy allowing the satisfaction of the requested performance with better battery usage. The evaluation results also demonstrate significant lifetime enhancements for the Li-ion battery, an increase of up to 20% as compared to the monosource based on a regular single battery.

Optimal architecture of the hybrid source (battery/supercapacitor) supplying an electric vehicle according to the required autonomy

The association of more than one storage system to ensure the supplying of the hybrid and electric vehicle became more and more useful by the cars manufacturers. The asked question in this case is the optimal amount of the deferent energy sources to ensure the mission with the best lifetime. The first parameter witch influence the architecture of the hybrid storage system is the required autonomy. This paper deals with the choice of the architecture and the sizing of the hybrid source composed with battery and supercapacitor packs according to the desired autonomy. In this case, two technologies of Li-ion battery (power and energetic technologies) are associated with the supercapacitor. The obtained result about the size and the ageing of the source will be compared to that obtained using only power technology of Li-ion battery to supply the vehicle.