Optimized EMS and a Comparative Study of Hybrid Hydrogen Fuel Cell/Battery Vehicles

This paper presents a new Fuel Cell Fuel Consumption Minimization Strategy (FCFCMS) for Hybrid Electric Vehicles (HEVs) powered by a fuel cell and an energy storage system, in order to minimize as much as possible the consumption of hydrogen while maintaining the State Of Charge (SOC) of the battery. Compared to existing Energy Management Strategies (EMSs) (such as the well-known State Machine Strategy (SMC), Fuzzy Logic Control (FLC), Frequency Decoupling and FLC (FDFLC), and the Equivalent Consumption Minimization Strategy (ECMS)), the proposed strategy increases the overall vehicle energy efficiency and, therefore, minimizes the total hydrogen consumption while respecting the constraints of each energy and power element. A model of a hybrid vehicle has been built using the TruckMaker/MATLAB software. Using the Urban Dynamometer Driving Schedule (UDDS), which includes several stops and accelerations, the performance of the proposed strategy has been compared with these different approaches (SMC, FLC, FDFLC, and ECMS) through several simulations

Optimized EMS and a Comparative Study of Hybrid Hydrogen Fuel Cell/Battery Vehicles

International audienceThis paper presents a new Fuel Cell Fuel Consumption Minimization Strategy (FCFCMS) for Hybrid Electric Vehicles (HEVs) powered by a fuel cell and an energy storage system, in order to minimize as much as possible the consumption of hydrogen while maintaining the State Of Charge (SOC) of the battery. Compared to existing Energy Management Strategies (EMSs) (such as the well-known State Machine Strategy (SMC), Fuzzy Logic Control (FLC), Frequency Decoupling and FLC (FDFLC), and the Equivalent Consumption Minimization Strategy (ECMS)), the proposed strategy increases the overall vehicle energy efficiency and, therefore, minimizes the total hydrogen consumption while respecting the constraints of each energy and power element. A model of a hybrid vehicle has been built using the TruckMaker/MATLAB software. Using the Urban Dynamometer Driving Schedule (UDDS), which includes several stops and accelerations, the performance of the proposed strategy has been compared with these different approaches (SMC, FLC, FDFLC, and ECMS) through several simulation

Intelligent Energy Management Strategy based on Artificial Neural Fuzzy for Hybrid Vehicle

International audienc

Design of Maximum Power Fuzzy Controller for PV Systems Based on the LMI-Based Stability

International audienceThis paper deals with a design methodology for stabilization of a class of nonlinear Photovoltaic (PV) systems. First, a nonlinear PV plant with a Takagi-Sugeno (TS) fuzzy model is presented. Then a model-based fuzzy controller design utilizing the concept of the Parallel Distributed Compensation (PDC) is employed. The proposed algorithm depends on the fuzzy reference model. The fuzzy control system consists of observer and fuzzy control components. The state observer does not require the system states to be available for measurement. Sufficient conditions are derived for stabilization is formulated in Linear Matrix Inequalities (LMIs). An application to PV system is given in this paper to illustrate the effectiveness of the proposed TS fuzzy controller and observer-design meth-odology. The simulation results demonstrate that the proposed fuzzy control sys-tem can guarantee the system stability and also maintain a good tracking perfor-mance

Robust and Predictive Energy Management Strategy based on Neuro-Fuzzy Approach for Hydraulic-Electric Hybrid Vehicles

Journees Automatique et Automobile (JAA

Fuzzy Maximum Power Tracking Control of PV Systems with Parametric Uncertainties

International audienceThis paper presents the new Robust Fuzzy Control (RFC) problem for uncertain nonlinear systems and also presents a Takagi-Sugeno (TS) fuzzy model-based maximum power control approach to enhance the efficiency and robustness of the solar photovoltaic (PV) power generation. First, the maximum-power-voltage-based control scheme and direct maximum power control scheme are introduced for the maximum power point tracking (MPPT). Furthermore, the MPPT robustness is also discussed to cope with varying atmosphere and system uncertainties. Second, the nonlinear system with parametric uncertainties is represented by the TS fuzzy model. Next, in order to reduce the number of measured signals, a TS fuzzy observer is established. Then, the concept of Parallel Design Compensation (PDC) is employed to design RFC from the TS fuzzy models. The sufficient conditions are formulated in the format of Linear Matrix Inequalities (LMIs) to obtain the observer and controller gains. The effectiveness of the proposed controller design methodology is finally demonstrated through a photovoltaic panel array to maximize the PV power. Therefore, the proposed method provides an easier implementation form under strict stability analysis

Energy Optimization Strategy based on Battery Fault Management for Hydraulic-Electric Hybrid Vehicle

International audienc

Hierarchical Energy Optimization Strategy and its Integrated Reliable Battery Fault Management for Hybrid Hydraulic-Electric Vehicle

International audienc

Real-Time Energy Management based on the Prediction of Hybrid Vehicle's Futures States

International audienc