Abstract:In this paper, an industrial grade adaptive control scheme is proposed for a micro-grid integrated dual active bridge driven battery management system (DIBMS). A benchmark industrial grade adaptive control scheme depends on two factors namely robustness and computational resource utilization when such controllers are implemented over processors. The mathematical model of DIBMS system is nonlinear, thus for desired response, non-linear controllers based on sliding mode variable structure control theory suits it… Show more
“…To further ensure the robustness and superiority of ATSMC, the experimental analysis has been considered by using HIL setup, which is basically the combination of both software in loop (SIL) and processor in loop (PIL). It is usually used for pre-evaluation before the final deployment of practical applications [41]- [44]. Figure 14 shows the HIL setup and test bench which includes both the controller hardware and the software setups.…”
The public awareness about global warming, emission of green-house gases and depletion of natural resources like oil and natural gas, are the main factors due to which fuel cell hybrid electric vehicles (FHEVs) have attained importance in automotive industry. Hard driving conditions like steep areas, slippery roads and rough terrains boost up the nonlinearities present in vehicle's model. The considered unified mathematical model of FHEV is based on fuel cell as a primary source, ultracapacitor and battery as storage units as well as the induction motor dynamics. The variations in parameters like resistance, capacitance, inductance and the nonlinearities of the dynamical system have also been considered. Three adaptation based nonlinear controllers namely adaptive terminal sliding mode, adaptive terminal synergetic and adaptive synergetic controllers have been proposed for the regulation of DC bus voltage along with speed tracking when subjected to European extra urban driving cycle. Lyapunov stability theory has been used to ensure global asymptotic stability of the system. Proposed controllers have been simulated on MATLAB/Simulink, where their comparison has been presented with each other and with recently proposed nonlinear controllers in the literature. Furthermore, ATSMC has further been implemented on real-time microcontroller hardware in the loop setup. The experimental results show that it provides better performance.INDEX TERMS Hybrid electric vehicles, adaptive terminal sliding mode control (ATSMC), adaptive terminal synergetic control (ATSC), adaptive synergetic control (ASC), hardware in the loop.
“…To further ensure the robustness and superiority of ATSMC, the experimental analysis has been considered by using HIL setup, which is basically the combination of both software in loop (SIL) and processor in loop (PIL). It is usually used for pre-evaluation before the final deployment of practical applications [41]- [44]. Figure 14 shows the HIL setup and test bench which includes both the controller hardware and the software setups.…”
The public awareness about global warming, emission of green-house gases and depletion of natural resources like oil and natural gas, are the main factors due to which fuel cell hybrid electric vehicles (FHEVs) have attained importance in automotive industry. Hard driving conditions like steep areas, slippery roads and rough terrains boost up the nonlinearities present in vehicle's model. The considered unified mathematical model of FHEV is based on fuel cell as a primary source, ultracapacitor and battery as storage units as well as the induction motor dynamics. The variations in parameters like resistance, capacitance, inductance and the nonlinearities of the dynamical system have also been considered. Three adaptation based nonlinear controllers namely adaptive terminal sliding mode, adaptive terminal synergetic and adaptive synergetic controllers have been proposed for the regulation of DC bus voltage along with speed tracking when subjected to European extra urban driving cycle. Lyapunov stability theory has been used to ensure global asymptotic stability of the system. Proposed controllers have been simulated on MATLAB/Simulink, where their comparison has been presented with each other and with recently proposed nonlinear controllers in the literature. Furthermore, ATSMC has further been implemented on real-time microcontroller hardware in the loop setup. The experimental results show that it provides better performance.INDEX TERMS Hybrid electric vehicles, adaptive terminal sliding mode control (ATSMC), adaptive terminal synergetic control (ATSC), adaptive synergetic control (ASC), hardware in the loop.
“…In this part, numerical simulations are presented to show the feasibility of the proposed strategy. Moreover, the experimental validation of the proposed control schemes is provided using processor in the loop experiment [28][29][30]. The simulated conversion system is based on 1.5 MW rated power.…”
Section: Numerical and Experimental Validationmentioning
confidence: 99%
“…Thus, the control algorithm is tested in real time. More details about processor in the loop experimentation are reported in [28][29][30]. More importantly, the controller validated using PIL testing is equally efficient when it is tested on an actual hardware plant [28].…”
Section: Processor In the Loop (Pil) Experimentationmentioning
confidence: 99%
“…More details about processor in the loop experimentation are reported in [28][29][30]. More importantly, the controller validated using PIL testing is equally efficient when it is tested on an actual hardware plant [28]. Thus, inspired from the above work, the proposed control schemes are tested using a processor in the loop (PIL) experiment and the block diagram of the setup is shown in Figures 22 and 23.…”
Section: Processor In the Loop (Pil) Experimentationmentioning
A permanent magnet synchronous generator (PMSG) in s grid-connected tidal energy conversion system presents numerous advantages such as high-power density and ease of maintenance. However, the nonlinear properties of the generator and parametric uncertainties make the controller design more than a simple challenge. Within this paper we present a new combined passivity-based voltage control (PBVC) with a nonlinear observer. The PBVC is used to design the desired dynamics of the system, while the nonlinear observer serves to reconstruct the measured signals. A high order sliding-mode based fuzzy supervisory approach is selected to design the desired dynamics. This paper addresses the following two main parts: controlling the PMSG to guarantee the maximum tidal power extraction and integrate into to the grid-side converter (GSC), for this the new controller is proposed. The second task is to regulate the generated reactive power and the DC-link voltage to their references under any disturbances related to the machine-side converter (MSC). Furthermore, the robustness of the controller against parameter changes was taken into consideration. The developed controller is tested under parameter variations and compared to benchmark nonlinear control methods. Numerical simulations are performed in MATLAB/Simulink which clearly demonstrates the robustness of the proposed technique over the compared control methods. Moreover, the proposed controller is also validated using a processor in the loop (PIL) experiment using Texas Instruments (TI) Launchpad.
“…Therefore, in the actual industrial design, the parameter of MOSFETs and diodes can be calculated based on the abovementioned maximum voltage and current stress to ensure safety. The above three controllers can use conventional proportional integral (PI) control method or other nonlinear control algorithms, such as sliding mode control (SMC) [31], [32], adaptive control [33], fuzzy control [34], model predictive control [35], and so on. Finally, these voltage references are modulated by the triangular carriers in the phase-shift pulse width modulation (PS-PWM) block, obtaining the gating signals to drive the MOSFETs.…”
To improve the operation performance and energy conversion efficiency of the redox flow battery (RFB), a modular active balancing circuit for redox flow battery applied in the energy storage system is proposed in this paper. Detailed topology description, parameter design, characteristic analysis, operation principle and control strategy of the proposed circuit are presented and discussed in the paper. Different from the conventional battery balancing circuit, the key point of the proposed balancing circuit is that it integrates the circulating pump driving circuit and the state-of-charge (SOC) equalization circuit of the redox flow battery. It uses the energy consumption of the pump driving to balance the SOCs of different battery stacks, which provides a new SOC balancing mechanism for RFB. Based on the proposed circuit, an active balancing control strategy using the time-sharing energy transmission method is proposed, in which the sub-modules of the circuit are alternatively configured in charge-state and discharge-state for absorbing energy or releasing energy to achieve the SOC balancing control for RFB. Compared with the conventional balancing solution or circuit, the proposed modular active balancing circuit simplifies the complexity of the battery management system for RFB, which has the advantages of high efficiency, high reliability, and good scalability. Simulations on Matlab/Simulink and experiments on a downscaled prototype were carried out to verify the feasibility and effectiveness of the proposed circuit and control strategy.INDEX TERMS Redox flow battery (RFB), active balancing circuit, battery management system (BMS), state-of-charge (SOC) balance, capacitive energy transfer.
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