Double Closed-Loop Charge-Discharge Control Strategy of VRB Based on CMAC

Today, the electricity industries are facing new challenges as the market is being liberalized and deregulated in many countries. Electricity storage is undoubtedly a disruptive technology that will play, in the near future, a major role in the fast developing distributed generations network. Indeed, electricity storage has many potential applications: management of the supply and demand of electricity, power quality, integration of renewable sources, improvement of the level of use of the transport and distribution network, etc. Over the years, many storage technologies have been investigated and developed, some have reached the demonstrator level and only a few have become commercially available. The pumped hydro facilities have been successfully storing electricity for more than a century; but today, appropriate locations are seldom found. Electrochemical storage is also an effective means to accumulate electrical energy; among the emerging technologies, the flow batteries are excellent candidates for large stationary storage applications where the vanadium redox flow battery (VRB) distinguishes itself thanks to its competitive cost and simplicity. In this ambitious work that encompasses the domains of electricity, electrochemistry and fluid mechanics, we have proposed a novel multiphysics model of the VRB. This model describes the principles and relations that govern the behaviour of the VRB under any set of operating conditions. Furthermore, this multiphysics model is a powerful means to identify and quantify the sources of losses within the VRB storage system; indeed, one of the purposes of this study is to propose strategies of control and operation for a greater effectiveness of the overall storage system. The electrochemical model is based on the electrochemical principles and the study of the VRB chemistry; this model determines the equilibrium voltage from the vanadium concentrations, and the associated activation, concentration, ohmic and ionic overpotentials. Furthermore, the vanadium concentrations within the tank and the stack are constantly determined as a function of the current and the electrolyte flowrate. A simplified model of the internal loss is also proposed. The electrochemical performance was then established through the simulation of a stand alone system composed of a solar source, a VRB and a load. The model determines the stack voltage, the power flows and the vanadium concentrations over a 24 h period. Furthermore, the model was successfully compared with experimental data through a series of charge and discharge cycles at constant currents. Thereafter, the properties of the electrolyte are briefly investigated: in particular their dependence upon the electrolyte composition. Indeed, the viscosity and the density are important parameters of the mechanical model. In order to analyse the battery performance, a mechanical model has been proposed to determine the mechanical power required to flow the electrolytes. This model based on fluid mechanics has an analytical part that predicts the pressure drop within the pipes and the tanks, and a numerical part. Indeed, the stack geometry is so complex that it can not be described analytically; therefore, a numerical model based on finite element method (FEM) is proposed. Hence, the mechanical power necessary to the battery operation is obtained at any operating conditions. The electrochemical and the mechanical models are finally assembled to form the original multiphysics model of the VRB. This model provides a good insight of the battery operation and offers a powerful means to enhance the battery performance. Indeed, there is at constant current an optimal flowrate that maximizes the efficiency. A second series of charge and discharge cycles has determined the efficiency of different control strategies. Finally, the battery operations at constant power were also discussed in details and an optimal operating point has been highlighted.

The vanadium redox flow battery (VRB) system involves complex multi-physical and multi-timescale interactions, where the electrolyte flow rate plays a pivotal role in both static and dynamic performance. Traditionally, fixed flow rates have been employed for operational convenience. However, in today’s highly dynamic energy market environment, adjusting flow rates based on operating conditions can provide significant advantages for improving VRB energy conversion efficiency and cost-effectiveness. Unfortunately, incorporating the electrolyte flow rate into conventional multi-physical models is overly complex for VRB management and control systems, as real-time operations demand low-computational and low-complexity models for onboard functionalities. This paper introduces a novel data-driven approach that integrates flow rates into VRB modeling, enhancing data processing capabilities and prediction accuracy of VRB behaviors. The proposed model adopts a gated recurrent unit (GRU) neural network as its fundamental framework, exhibiting exceptional proficiency in capturing VRB’s nonlinear voltage segments. The GRU network structure is carefully designed to optimize the predictive ability of the model, with flow rate considered as a crucial input parameter to account for its influence on VRB behavior. Model refinement involves analyzing well-designed simulation results obtained during VRB operations under various flow rates. Laboratory experiments were also designed and conducted, covering different conditions of currents and flow rates to validate the proposed data-driven modeling method. Comparative analyses were performed against several state-of-the-art algorithms, including equivalent circuit models and other data-driven models, demonstrating the superiority of the proposed GRU-based VRB model considering flow rates. Thanks to the GRU’s outstanding capability in processing time series data, the proposed model delivers impressively accurate terminal voltage predictions with a low error margin of no more than 0.023 V (1.3%) under wide operating ranges. These results indicate the efficacy and robustness of the proposed approach, highlighting the novelty and significance of accounting for flow rates in accurate VRB modeling for management and control system design.

With the development of wind power technology in recent years, wind power technology has made rapid development. In this paper, the wind farm is the main object of study, the energy storage elements is vanadium redox flow battery (VRB), the use of decoupling control of fuzzy PID control algorithm for real-time changes in PID parameters of the active and reactive power. The outer loop of motor side rectifier is power loop, the inner is current loop. The outer loop of grid side inverter is the voltage loop, the inner is current loop, and based on vector control, the rectifier and inverter achieve decoupling process.The traditional PID is poor in anti-interference ability and robustness,so this paper uses the fuzzy PID control algorithm. The MATLAB/simulation results show that the fuzzy control algorithm can achieve power tracking control,and has strong robustness.

A control scheme of ANN-based PID controller is developed here to reach high precision tracking control for an electro-hydraulic servo system. The PID controller is used as a feedback controller to guarantee the system stability. The cerebellar model articulation controller (CMAC) neural network is used as a feed-forward compensator to identify the inverse system dynamics model. The CMAC and the PID controller are connected in parallel. The outputs of this paralleled controller are summed up as the total control action. A nonlinear tracking differentiator (NTD) is presented to yield high quality differential signals for the PID controller. The main task of this control algorithm is to make the error between the total control action and the output of the CMAC minimize by the CMAC learning algorithm. Thus the control action is formed by the CMAC. Numerical simulation results show comparing with conventional PID control strategy this proposed control scheme has an excellent system performance including high precision trajectory tracking ability and rejection of disturbance.

The double closed loops control strategy composed of inner current loop and outer voltage loop in the d-q synchronous frame is a relatively common control strategy of the three-phase voltage-sourced PWM rectifier. The system can not be completely decoupled because of the variable inductance in the actual system. And for simple, the decoupled part of the controller is usually ignored. What's more, the equation of the outer voltage loop is nonlinear. According to the analysis of the model of the rectifier, a novel double closed loops control strategy composed of inner current loop in the complex vector and outer square of the voltage loop, is proposed. The inner current loop using the mentioned control strategy can be completely decoupled without the exact value of the boost inductance, and the equation of the outer square of the voltage loop is linear. From the results of the simulation, the mentioned control strategy can greatly improve the dynamic and static of the system.

With a rapid charge/discharge feature, vanadium redox flow batteries (VRBs) are green, large-scale energy storage devices useful for power smoothing in unstable renewable power generation facilities, such as those involving solar and wind energy. This study developed a VRB model to establish a relationship between electrolyte concentration, equilibrium potential, and state of charge (SOC), to simulate the dynamic responses in charge/discharge cycles of the electrolyte concentration, terminal voltage, and SOC, and to evaluate the internal loss and battery efficiency. The proposed model not only serves as the basis of a dynamic analysis tool for future studies for designing a large-scale VRB but also reveals the time-varying electrolyte status for a long-term VRB operation.

There is an increasing trend in using exoskeleton to walk or carry payload. In the process of human-exoskeleton interaction, since the user's intention is required accurately, an important problem is human-robot collaborative control. A precise position control strategy will significantly enhance collaboration between the exoskeleton and the user. This paper proposes a novel method combining sliding mode control (SMC) with Cerebellar model articulation controller (CMAC). The proposed method is applied in a lower extremity exoskeleton to track a desired trajectory. The switching surface in sliding mode control was determined by tracking error. A CMAC was designed as a compensator which considers uncertainty of the dynamical model. The dynamic of the lower extremity is derived by using Euler-Lagrange Equation. The proposed control strategy was proved stable with Lyapunov analysis and used for trajectory tracking in comparison with a conventional sliding mode control. Results with Matlab simulation shows that the proposed controller can achieve better tracking capability and robust performance.

Compared to conventional n-phase topologies, the n-phase (n+1)-leg inverters are able to work under unbalanced loading conditions. This paper investigates the control strategy of a five-phase six-leg inverter system with unbalanced loads. Based on the third-harmonic injection pulse-width modulation (PWM) method, a double-closed loop control scheme with inner current loop and outer voltage loop is applied. Compared to an open five-phase five-leg inverter system, the designed system can balance the output multi-phase voltage with unbalanced loads, then realizing the required power distribution of different phases. Meanwhile, the generalized Park transformation is utilized in the controller to convert the referenced coordinate system to a rotating one from a natural coordinate system, which contributes to make the control system have a satisfied performance. Finally, the PLECS-based simulation verifies the designed strategy.

A mode-free airship altitude control strategy is proposed based on Q-learning algorithm and CMAC (Cerebellar Model Articulation Controller) network. First, we designed an adaptive method to establish MDP (Markov Decision Process) model of airship altitude control on the foundation of analyzing actual motions. Then, control strategy is learned online via Q-learning algorithm, and CMAC network is used to generalize the value function of action. Finally, typical control tasks are carried out using a simulated low altitude airship. Control strategy could be worked out without access to airship accurate dynamic model. Results show that the airship's MDP model parameters using the adaptive method are better matched with each other than using simple equally divided method, and CMAC networks could accelerate converge of algorithm. Control strategy's effectiveness and stability is demonstrated by comparing with a PID controller.

This study entailed applying image-processing techniques and an intelligent control method to a wheeled mobile robot (WMR) for real-time trajectory recognition and tracking. The WMR was fitted with a charge-coupled device (CCD) camera to capture images of the environment, and the hue-saturation-intensity color space was used to classify the color features of the captured images. The WMR calculates the relative position of a target object by using image-processing and edge-detection algorithms. This paper proposes a cerebellar model articulation controller (CMAC) and adaptive CMAC to replace conventional proportional-integral-derivative (PID) controller for guiding the WMR to track a desired path. Moreover, using Lyapunov's stability theory to optimize the learning rate ensures that the proposed control system is stable. The tracking performance of several controllers used to track various path patterns were compared. Finally, according to the theoretical analysis, simulations, and experimental results of this study, the proposed control scheme is effective.

Sensorless parameter estimation of vanadium redox flow batteries in charging mode considering capacity fading

Three-phase voltage PWM rectifier is a multivariable, strong coupling, nonlinear multi-input and multi-output system. In the design of rectifier control systems, with PI control it is difficult to achieve the ideal control effect, the dynamic performance is poor, and the parameter computation is complex. Moreover, the traditional sliding mode control voltage outer loop suffers from the problem of chattering, which is difficult to solve. Responding to the above issues, a new type of variable speed reaching law is proposed, which is applied to the voltage outer loop sliding mode control, while the feedback linearization principle is introduced to the current inner loop, and a new type of double closed-loop sliding mode control system is obtained by applying the two theories to the design of the sliding mode controller. A simulation model is established in MATLAB/Simulink to compare the PI control, the SMC control and the V-SMC control strategy proposed in this paper (voltage outer loop V-SMC current inner loop FLC-SMC control), and the simulation results show that the rectifier under the new dual-closed-loop sliding mode control strategy has the advantages of good dynamic performance, strong robustness and strong anti-interference ability. At the same time, compared with the traditional sliding mode control strategy, the vibration suppression effect under the proposed control strategy is obvious. Finally, a 10 kW rectifier control system is built on a semi-physical hardware-in-the-loop experimental platform to further verify the correctness and superiority of the proposed control strategy.

Electric Springs (ESs) can effectively solve the problem of load side voltage instability caused by the voltage fluctuation on the grid side. Although the single closed-loop control strategy based on the root mean square (RMS) value of the voltage at the point of common coupling (PCC) can maintain the PCC voltage stability, the harmonics on the load side and the ES output voltage will be distorted largely. In this paper, a double closed-loop control strategy with an outer voltage loop and an inner current loop is proposed to address the problem mentioned above. The simulation results show that the improved double closed-loop control strategy can effectively suppress the harmonics on the PCC voltage as well as the ES output voltage.

Ultrasonic motors (USMs) are widely used in many applications that precise and fast motions are required, such as precision machines and medical devices, etc. In this paper, a USM -driven ear surgical device is introduced. To address the control challenges of the USM, an intelligent controller consisting of a cerebellar model articulation controller (CMAC) and a sliding mode compensator (SMC) is designed. Therein, the CMAC serves as the main controller due to its fast learning ability while the SMC is used to eliminate the approximation error between the CMAC and the desired perfect controller. Several experiments are carried out to validate the effectiveness of the proposed control scheme, and the results show that the proposed control scheme is able to achieve good tracking performance and guaranteed robustness.

This paper discusses adaptive control method used in high performance servo system based on Cerebellar Model Articulation Controller(CMAC). It analyzes the uncertain and nonlinear factors of the servo system, studies the modeling method using the frequency property of the system, and then uses an additional item to instead of the non-modeling factor. In the proposed control scheme, the CMAC controller is able to learn the unknown model dynamics, parameter variation and disturbance of the system on line. The model reference adaptive control (MRAC) scheme is used to give better solutions with online adaptation. It contemporarily improved the conception mapping algorithm of the Cerebellar Model Articulation Controller Neural Network(CMACNN), which gave a determined expression of the physical memory size and designed a physical memory address function. Experiment results verify that the proposed strategy can achieve high tracking precision for real-time position close-loop servo system.