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This paper presents the development and implementation of a system supervisory controller in a hydrogen-based fuel cell electric vehicle. The controller's primary function is to ensure the safe control of the fuel cell system processes while facilitating coordination among various subsystems, including the balance of plant subsystems, vehicle control unit, diagnosis unit, and powertrain. The supervisory controller comprises of three primary parts: a State Machine, an Optimal Setpoint Generator, and a Power Limit Calculator. The State Machine, which serves as the central part of the supervisory controller, coordinates the fuel cell system's different operational states, including the complex processes of start-up and shutdown. To maximize the fuel cell system's efficiency and minimize the stack's degradation, the Optimal Setpoint Generator produces the subsystem's setpoints by solving an optimization problem and considering the manufacturer's requirements. The Power Limit Calculator assesses the stack's power output capability and calculates the current setpoint for the DC/DC converter. It then provides this data to the Energy Management System (EMS), which oversees the distribution of power between the fuel cell system and the batteries. The proposed fuel cell system supervisory controller is verified using the Worldwide Harmonized Light Vehicles Test Cycles (WLTC) in a real-world car. The designed control structure is implemented in a prototype hydrogen-based electric car at both PowerCell and CEVT facilities under the framework of the INN-BALANCE Horizon 2020 European project. • State machine-based supervisory controller for fuel cell system is designed. • The designed control structure is implemented in a prototype hydrogen-based vehicle. • The controller comprises: State Machine, Setpoint Generator, Power Limit Calculator. • The proposed control structure handles the startup and shutdown process of PEMFC. • Minimizing stack degradation by implementing a fuel cell power limit calculator. [ABSTRACT FROM AUTHOR]

ASHRAE RP-1747 is a CO 2 -based demand-controlled ventilation (DCV) approach which uses trim and respond logic to dynamically adjust variable air volume (VAV) terminal units' minimum airflow setpoints based on zones' ventilation requirements. While simulation results and laboratory testing have estimated the impact on heating, ventilation, and air conditioning (HVAC) systems compared to traditional ventilation, there have been limited applications of RP-1747 in occupied, real-world buildings to date. This paper introduces a real-world implementation of RP-1747 DCV in an institutional office building over an eight-month period, using a supervisory control approach. During this implementation, a complementary temperature setback approach was also developed and employed in the case study building. These changes to the sequences of operation, as well as corrections to other sub-optimal sequences of operation discovered during implementation, resulted in a 36 ± 2 % and 2 ± 6 % reduction in heating and cooling energy use, respectively, while improving per person ventilation rates in the case study. The results aim to contribute to the body of literature on this emerging DCV approach and provide anecdotal evidence of its benefits and interactions with other control logic in a real-world application, while also demonstrating the benefits of supervisory control when implementing complex process control functions. [ABSTRACT FROM AUTHOR]

Equal power-rating inverters operating with different power set-points in either an islanded or grid-connected mode may lead to inter-unit circulating power caused by a large mismatch between power generation and demand during network contingencies (faults on the heavy load side or unintentional islanding). This circulating power may violate the dc-link voltage limit and, as a result, the protection scheme may shut down the inverter and reduce the microgrids reliability. This paper proposes a regulator for controlling the dc-link voltage of the microgrid's inverter during a period of circulating power. It includes a discharging resistor with a series-connected switch across the dc-link capacitor which is turned on through a control algorithm if the dc-link voltage exceeds its pre-defined limit. Case studies of parallel-connected inverters are conducted and their stability assessed through a small-signal analysis. In addition, a realistic microgrid is designed as a low-voltage (LV) network and tested to verify the concept and regulator actions presented. The simulation results validate the effectiveness of the proposed regulator during network contingencies. [ABSTRACT FROM AUTHOR]

This paper focuses on dynamic modeling, simulation, control and energy management in an agricultural experiment station located at Sahline–Tunisia consisting of a 1.5 kW photovoltaic panel (PV) and a 25 A h Lead Acid battery storage supplying an induction motor coupled to a centrifugal pump as mechanical load. The cost-optimally design and the new suitable power management approach are the two main objectives. An iterative optimization approach namely, the Deficiency of Power Supply Probability (DPSP), the Relative Excess Power Generated (REPG), the Energy Cost (EC) as well as the Total Net Present Cost (TNPC) have been developed in order to find the optimal configuration of PV/battery. To reach the second object, three new supervisory controllers are designed, a neuro-fuzzy controller, a fuzzy controller and an algorithm controller. In order to show the effectiveness of the first one, a comparison of the three controllers is proposed. The principal objectives of the three supervisory controllers are: (i) the design of an adequate tracking system maximum power point (MPPT) to extract the maximum power which is given by the theory of conservation of energy, (ii) the insurance of the control speed needed for the vectorial control of the induction motor, (iii) the regulation of the water in the tank which is taken as a second storage system and finally (iv) the insurance of the correct operation for all the conversion string in order to optimize the quantity of water pumped. [ABSTRACT FROM AUTHOR]

Abstract: This study presents paper presents an analysis of the potential CO2 savings that could be gained through the introduction of hydrogen-powered fuel cells on a commuter-style railway route. Vehicle is modelled as a fuel cell series hybrid. The analysis consists of power/energy flow models of a fuel cell stack, battery pack and hybrid drive controller. The models are implemented in a custom C# application and are capable of providing key parametric information of the simulated journey and individual energy drive components. A typical commuter return journey between Stratford Upon Avon and Birmingham is investigated. The fuel cell stack and battery pack behaviour is assessed for different stack sizes, battery sizes and control strategies to evaluate the performance of the overall system with the aim of understanding the optimum component configuration. Finally, the fuel (H2) requirements are compared with typical diesel and hybrid-diesel powered vehicles with the aim of understanding the potential energy savings gained from such a fuel cell hybrid vehicle. [ABSTRACT FROM AUTHOR]

Abstract: This paper attempts to propose a hybrid adaptive cerebellar model articulation controller (CMAC) sliding mode control (SMC; called HAC-SMC) with a supervisory controller for a class of nonlinear system, in which the HAC composed of a direct adaptive CMAC and an indirect adaptive CMAC control is performed as the SMC. There are two methods to design the switching control law of SMC. One is the sign switching controller. The other is the CMAC switching controller. Besides, a supervisory controller is appended to the HAC-SMC to guarantee the states staying in the boundary layer. The adaptive laws of the control system are derived in the sense of Lyapunov theorem so that the asymptotic stability of the system could be guaranteed. Simulation results show that the proposed control system has satisfactory performance on the inverted pendulum system and the Chua''s chaotic circuit. [Copyright &y& Elsevier]