Triple Phase Shift Modulation Research Articles

Triple Phase Shift Modulation Scheme for Bidirectional Wireless Power Transfer Systems With Efficiency Maximization

Triple Phase Shift Modulation Scheme for Bidirectional Wireless Power Transfer Systems With Efficiency Maximization

Performance Analysis of Electric Vehicle Fast Charging System with Dual Active Bridge Converter using Triple Phase Shift Modulation

Performance Analysis of Electric Vehicle Fast Charging System with Dual Active Bridge Converter using Triple Phase Shift Modulation

Topology and Control Optimization of Bidirectional DC/DC Converter for Electric Vehicles

With the rapid development of intelligent electric vehicles, the number of electrical equipment increases, and the interconnection and energy transmission between on-board DC buses has become urgent. This paper proposes a partial isolated bidirectional converter based on dual active bridge converter. By partial switch sharing, the converter has a simplified structure and can supply energy to DC loads of different voltage levels. The system adopts a hybrid control strategy of pulse width modulation and triple phase shift modulation, and introduces a fundamental phase shift to reduce coupling between variables. The operation process is analyzed, and the models of transmitted power, current stress and soft-switching range under two typical operation modes, corresponding to the full load and light load, are established respectively. Under wide gain and different power distribution conditions, the multi-objective optimization is realized. Finally, the correctness of theoretical analysis is verified by experiments.

The Generalization of Bidirectional Dual Active Bridge DC/DC Converter Modulation Schemes: State-of-the-Art Analysis under Triple Phase Shift Control

The main objective of this paper is to provide a thorough analysis of currently used modulation control schemes for single-phase bidirectional dual active bridge DC/DC converters. In this article, it will be shown that single phase shift, extended phase shift and dual phase shift modulation schemes are special cases of the triple phase shift (TPS) modulation scheme. The article aims to highlight six TPS switching modes and their complements with operational constraints. Unlike previous studies that regarded TPS as a complex scheme, this paper simplifies the analysis of each mode and aims to standardize the understanding of TPS modulation for dual active bridge (DAB) converters. Power equations, range of power transferred and zero-voltage switching (ZVS) are derived for all the modes under TPS without assuming fundamental component analysis. Additionally, a generic optimization algorithm is developed to show the advantages of TPS modulation, and thus, the analysis in this paper offers a valuable insight for single-phase DAB converter designers in identifying a wide range of optimization algorithms to achieve higher efficiency under TPS modulation. This analysis contributes to the advancement of bidirectional DAB converter technology and facilitates its application in various power electronic systems.

Maximum Efficiency Tracking and ZVS Realization for Wide Output Voltage Range Employing Segmented TPS Modulation Scheme

The efficiency of wireless power transfer (WPT) systems is highly dependent on the load and dc voltage gain, which may change in a wide range in electric vehicle (EV) charging applications. Besides, existing control triple-phase-shift (TPS) strategies aimed at power regulation, zero-voltage switching (ZVS) realization and maximum efficiency point tracking (MEPT) have limitations when applied to the wide output voltage application. To fill this gap, a segmented TPS modulation scheme is proposed. Considering wide-range ZVS, three different working modes are derived to achieve MEPT over the wide output voltage range. The proposed modulation scheme employs closed-loop control by integrating different working modes. In addition, the efficiency-oriented seamless transition method among different working modes is described, which can avoid the transient oscillation at the boundary of the mode transition. The proposed modulation scheme's on-state loss and switching loss are compared to the traditional TPS modulation scheme. Finally, a 1.5 kW prototype has been built to verify effectiveness of the proposed modulation scheme within the wide voltage range, and the measured efficiency can be increased by up to 0.82% in the deep buck mode and 2.20% in the deep boost mode.

Artificial-Intelligence-Based Triple Phase Shift Modulation for Dual Active Bridge Converter With Minimized Current Stress

The dual active bridge (DAB) converter has been popular in many applications for its outstanding power density and bidirectional power transfer capacity. Up to now, triple phase shift (TPS) can be considered as one of the most advanced modulation techniques for DAB converter. It can widen zero voltage switching range and improve power efficiency significantly. Currently, current stress of the DAB converter has been an important performance indicator when TPS modulation is applied for smaller size and higher efficiency. However, to minimize the current stress when the DAB converter is under TPS modulation, two difficulties exist in analysis process and realization process, respectively. Firstly, three degrees of modulation variables in TPS modulation bring challenges to the analysis of current stress in different operating modes. This analysis and deduction process leads to heavy computational burden and also suffers from low accuracy. Secondly, to realize TPS modulation, if a lookup table is adopted after the optimization of modulation variables, modulation performance will be unsatisfactory because of the discrete nature of lookup table. Therefore, an AI-based TPS modulation (AI-TPSM) strategy is proposed in this paper. Neural network (NN) and fuzzy inference system (FIS) are utilized to deal with the two difficulties mentioned above. With the proposed AI-TPSM, the optimization of TPS modulation for minimized current stress will enjoy high degree of automation which can relieve engineers’ working burden and improve accuracy. In the end of this paper, the effectiveness of the proposed AI-TPSM has been experimentally verified with a 1 kW prototype.

Improved Triple-Phase-Shift Modulation for Bidirectional CLLC Converters

CLLC resonant converters are an attractive option for battery charging applications due to their bidirectional power flow and high efficiency. Pulse frequency modulation (PFM) is the simple method to drive CLLC converters. However, PFM cannot regulate the output voltage under the light-load condition properly, which leads to high switching and core losses. Phase shift modulation techniques like dual-phase shift (DPS) modulation can overcome this challenge. However, more improvements are demanded due to high circulating currents in phase shift modulations. In this paper, an improved modulation technique based on triple-phase shift (TPS) has been applied in CLLC converters to improve the light-load efficiency. TPS modulation like any other phase-shift modulation, keeps the switching frequency of CLLC converters fixed at the resonant frequency under the light-load condition and regulates the output voltage by its three phase shift parameters. The improved TPS modulation has lower circulating current at the same average output current compared to DPS modulation. Therefore, higher efficiency, smaller peak, and RMS current values can be achieved under the light-load condition. In addition, the proposed TPS modulation has a better flexibility in regulating the output voltage under the light-load condition due to an extra phase shift parameter compared to DPS modulation. The proposed TPS modulation has been analyzed thoroughly in this paper and a proper selection of phase shift values has been explained to improve the efficiency of the converter. Finally, advantages of the improved TPS modulation have been validated by simulation and a 1 kW experimental setup.

Analytical and Normalized Equations to Implement the Optimized Triple Phase-Shift Modulation Strategy for DAB Converters

A fully normalized algorithm to implement the optimal triple-phase shift (TPS) modulation strategy of the dual active bridge converter is proposed in this paper. The algorithm evaluates three simple expressions that fit the optimal solutions obtained in recent works, which allows the algorithm to be implemented in real-time and valid for the whole operating range. As a result, the converter operates under zero voltage switching conditions and minimizes conduction losses. In addition, the algorithm considers the minimum current required to guarantee zero voltage switching condition that faces undesired dead-band of switching devices effect. The proposal achieves soft transition between any operation region and fast closed-loop response with no stability concern, presenting robustness under leakage inductance deviation. Finally, the algorithm presented in this paper is verified with a 4 kW experimental prototype. Experimental results show that the algorithm proposed can be evaluated with less than 2.8 μs and allows soft transition between any operation region to be achieved. Besides, fast closed-loop changes of 750 μs through all the operating ranges, keeping minimum RMS current under zero voltage switching, are shown.

Autonomous Input Voltage Sharing Control and Triple Phase Shift Modulation Method for ISOP-DAB Converter in DC Microgrid: A Multiagent Deep Reinforcement Learning-Based Method

This article proposes a multiagent (MA) deep reinforcement learning (DRL) based autonomous input voltage sharing (IVS) control and triple phase shift modulation method for input-series output-parallel (ISOP) dual active bridge (DAB) converters to solve the three challenges: the uncertainties of the dc microgrid, the power balance problem, and the current stress minimization of the converter. Specifically, the control and modulation problem of the ISOP-DAB converter is formed as a Markov game with several DRL agents. Subsequently, the MA twin-delayed deep deterministic policy gradient (MA-TD3) algorithm is applied to train the DRL agents in an offline manner. After the training process, the multiple agents can provide online control decisions for the ISOP-DAB converter to balance the IVS, and minimize the current stress among different submodules. Without accurate model information, the proposed method can adaptively obtain the optimal modulation variable combinations in a stochastic and uncertain environment. Simulation and experimental results verify the effectiveness of the proposed MA-TD3-based algorithm.

Unifying the Transformer Current in Multiple Phase Modulation Without Current Spike During Load Transients

To accelerate the dynamic response in a dual active bridge converter, feed-forward control can be applied in parallel to the conventional PI controller for closed-loop control. The transformer current thus changes significantly due to the phase shift change. A current spike can appear during load transients, particularly when using multiple phase shift modulation. Effort has been made in the previous literature to implement active compensation between two different steady-state operations to eliminate the transformer current spike; however, this results in a complicated control structure. This letter thus proposes a novel modulation method unifying the transformer current for dual phase shift and triple phase shift modulation to mitigate the transformer current spike when switching among various phase shift controls during load transients. By applying the proposed pulsewidth modulation strategy, the instantaneous value of the transformer current stays the same at the beginning of the switching period even with different steady-state modulation techniques. Also, full-operation-range zero-voltage switching can be realized for the primary side or the secondary side switches by combining with the proposed modulation strategy. An experimental prototype demonstration validates the proposed modulation strategy.

Simplified Closed-Form Optimized Trajectories Control for a Dual Active Bridge Converter With ZVS Implementation Over Whole Domain

A dual active bridge converter is widely used in electric vehicle charging systems and other fields for its excellent features. Despite the diversity of relevant studies on the triple-phase-shift (TPS) modulation, the existing investigations fail in the zero-voltage-switching (ZVS) implementation over the whole voltage and load domains, especially in the transition process between different modes. To address the current state of research, the magnetic current is introduced to bridge the ZVS gap between different modes in this article. A simpler method of the acceptable maximal magnetic inductance design in view of the current stress and the transformer's turns ratio is presented. Afterward, the evaluation method of system efficiency over the full voltage range is raised. Most critically, the simplified optimal control trajectories considering the impact of the magnetic current are proposed for the first time for the TPS modulation, eliminating the nonmonotonicity and leapfrogging of the control variables. Compared with the existing works, the method proposed in this article accomplishes ZVS over the whole domain, thereby reducing potential electromagnetic interference and enhancing the efficiency. Eventually, the proposed method is verified by a 1.0-kW prototype.

FEA Based Transformer Loss Analysis for Dual Active Bridge DC–DC Converter Using Triple Phase Shift Modulation

High-frequency transformers are a key component of dual active bridge (DAB) dc–dc converters, providing isolation and voltage scaling. The losses in the transformer should be minimized to improve efficiency and extend lifetime. The existing research focuses on the optimization of design parameters, such as core material, cross-sectional area and winding configuration to minimize losses. However, the transformer losses also depend on the harmonic content of the current as well as the design parameters and thus the efficiency can be further improved by selecting a modulation scheme which results in minimum current harmonics. This article evaluates the effect of modulation schemes on the transformer losses of a DAB converter operating under triple phase shift (TPS) modulation using finite element analysis. A comparison of losses under different modes of TPS modulation has been provided and it is proven that losses can be significantly reduced by selecting optimal modulation schemes. The experimental results performed on a 1-kW DAB converter laboratory prototype are provided to validate the proposed work. Moreover, a generalized framework has been proposed to analyze and optimize transformer losses for isolated converters.

Triple-Phase Shift Modulation Scheme of DAB Converter With LCL Resonant Tank

In this article, an optimized triple-phase shift (TPS) modulation scheme is proposed for the dual active bridge (DAB) converter with an inductor–capacitor–inductor (LCL) resonant tank. By using the fundamental harmonic analysis (FHA), the working modes and the conduction loss are analyzed. The conduction loss is associated with the equivalent resistance of the components and the voltage conversion ratio. On the premise of the zero-voltage-switching (ZVS), the control scheme for optimizing the conduction loss is proposed with three degrees of freedom. The control law and the closed-loop control are analyzed for bidirectional power flow. Furthermore, the conduction loss is analyzed and compared with the previous dual-phase shift (DPS) control strategies. It demonstrates the lower conduction loss in the optimized TPS modulation scheme. Finally, the performance of the control strategy is verified by a 1 kW experimental prototype.

Research on Reactive Power Optimization Control of a Series-Resonant Dual-Active-Bridge Converter

In order to meet the demands of the bidirectional transmission of electric vehicle charger power, a series-resonant dual-active-bridge (DAB) converter is investigated in this paper. Firstly, the active and reactive power and zero voltage switching (ZVS) conditions of the full-bridge arm under extended phase-shift modulation, dual phase-shift modulation and triple phase-shift modulation are analyzed. Secondly, with the minimum reactive power as the optimization objective, the extended phase shift (EPS) is finally selected as the modulation method after comparing the minimum reactive power under various modulation methods when the normalized value of active power is varied in the range of 0–1. By constructing the objective function and determining the constraints, an off-line reactive power–minimization control strategy is proposed to achieve the ZVS of the full-bridge arm and, finally, the feasibility of the proposed control strategy is verified by simulation and experiment.

Automatic Triple Phase-Shift Modulation for DAB Converter With Minimized Power Loss

Currently, triple phase-shift (TPS) modulation has attracted more and more attention of researchers as an advanced modulation strategy for dual active bridge converter (DAB). Since it has three degrees of freedom, it can realize better performance both in soft switching ranges and power efficiency. However, how to choose these three degrees of freedom to realize optimal power efficiency of DAB converter becomes a concern for researchers. Generally, there exist two difficulties to apply efficiency-oriented TPS modulation. The first difficulty lies in the analysis process in which the main task is to figure out the relationships between modulation parameters and power loss. The three modulation parameters in TPS bring difficulties in analysis and deduction process, which suffers from high computational burden and low accuracy. Additionally, the second difficulty lies in the real-time realization of TPS modulation. If a look-up table is applied to store the optimized modulation parameters, it is highly likely that its discrete nature will result in unsatisfactory modulation performance. Therefore, this article proposes an efficiency-oriented automatic TPS (ATPS) modulation approach, which utilizes neural network, particle swarm optimization, and fuzzy inference system, respectively, in its three stages. The proposed ATPS is able to mitigate labor in computational burden with a highly automatic fashion. Finally, this proposed ATPS has been validated with 1-kW hardware experiments.

Closed-Loop Black Start-Up of Dual-Active-Bridge Converter With Boosted Dynamics and Soft-Switching Operation

This letter proposes a closed-loop black start-up control for the dual-active-bridge (DAB) converter. With a simple combination of the extended phase-shift and triple phase-shift modulation schemes, the DAB converter can start up with the maximum allowable precharge current while realizing soft-switching operation in the trapezoidal current mode simultaneously. Compared to the conventional start-up procedure that usually requires multiple steps of operation and parameter fine-tuning, the proposed start-up method can be implemented simply into the existing closed-loop controller and can shorten the start-up transients of the DAB converter significantly. The presented methods are validated experimentally on a downscaled DAB converter prototype.

Frequency-Domain Modeling of Dual-Active-Bridge Converter Based on Harmonic Balance Approach

The dual active bridge (DAB) converter contains both ac and dc states. Hence, state-space average modeling of DAB is intricate. In the literature, several models of DAB have been developed to reconstruct the ac state. However, full-order models provide better accuracy than reduced order models. Frequency-domain-based modeling captures the total behavior of the converter, such as generalized average modeling (GAM) or series-based solutions. However, with the consideration of more harmonics in the model, derivation of state equations and, thus, state matrices become tedious. This article proposes a harmonic state-space (HSS) modeling framework for DAB that overcomes earlier obstacles and accurately models both the ac and dc states depending on the inclusion of the number of harmonics in it. The modeling framework described here is applicable to single, dual, and triple phase-shift modulation schemes. This modeling framework presents a straight forward approach and has a definite structure, which presents flexibility and ease in deriving the input–output relationship. Both large-signal and small-signal models are derived and analyzed. This model is validated by time-domain simulation, performed on MATLAB/Simulink. Experimental investigations on a prototype of DAB also validate this model.

Model Predictive Control With Triple Phase Shift Modulation for a Dual Active Bridge DC-DC Converter

A fast dynamic response is one of the key demands for the dual active bridge (DAB) dc-dc converter to achieve a well-regulated output voltage over a wide range of operating conditions. Recently, model predictive control (MPC) has become a promising alternative to achieve fast dynamic response when compared to other classical converter control techniques. This paper presents an MPC based control approach augmented with a current stress optimized scheme based on triple phase shift (TPS) modulation to improve the dynamic performance and maintain a desired output voltage level without violating a minimum current stress constraint. A prediction model has been developed to accurately predict the dynamic behavior of the output voltage in the next horizon under the input voltage variations and load disturbances. As the model is developed using the TPS modulation thus inner phase shifts of the H-bridges as well as system's states are required to solve the formulated control problem. The inner phase shifts of the H-bridges are calculated using current stress optimized TPS scheme. Simulation and experimental results are provided to demonstrate the merits of the proposed control algorithm which includes a fast dynamic response without no overshoots in the output voltage, fixed switching frequency, low computational complexity and high degree of robustness.

A Low Complexity Algorithm for Efficiency Optimization of Dual Active Bridge Converters

This paper proposes a triple phase shift modulation (TPS) with an optimization technique that aims at maximizing the efficiency of the dual active bridge converter. Such a converter is often used to interface renewable or energy storage systems in smart dc power systems, where loss minimization via TPS is crucial, especially at light-load conditions. In this paper, favorable modulation parameters are found first, aiming at minimum rms currents and zero voltage switching, by considering only some fundamental converter parameters, namely, the input and output voltages, the transformer ratio, and the leakage inductance. Then, on the basis of the closed-form analytical description of the converter behavior over the determined modulation patterns, trajectories in the modulation planes that are capable of improving the total efficiency are identified. It is shown that such trajectories lead to close-to-optimal efficiency operation, which can be exploited to implement fast perturb-and-observe methods requiring just minimal converter parameters knowledge. The results are verified experimentally on a 1.5-kW prototype. It is shown that the proposed approach achieves close-to-optimal efficiency operation under different input voltages, being the error with respect to the measured optimal points obtained by a brute-force approach lower than about 0.2%.

Reinforcement Learning Based Efficiency Optimization Scheme for the DAB DC–DC Converter With Triple-Phase-Shift Modulation

Aim to improve the power efficiency of the dual-active-bridge (DAB) dc–dc converter, an efficiency optimization scheme with triple-phase-shift (TPS) modulation using reinforcement learning (RL) is proposed in this article. More specifically, the Q-learning algorithm, as a typical algorithm of the RL, is applied to train an agent offline to obtain an optimized modulation strategy, and then the trained agent provides control decisions online in a real-time manner for the DAB dc–dc converter according to the current operating environment. The main objective is to obtain the optimal phase-shift angles for the DAB dc–dc converter, which can achieve the maximum power efficiency by reducing the power losses. Moreover, all possible operation modes of the TPS modulation are considered during the offline training process of the Q-learning algorithm. Thus, the cumbersome process for selecting the optimal operation mode in the conventional schemes can be circumvented successfully. Based on these merits, the proposed efficiency optimization scheme using the RL can realize the excellent performances for the whole load conditions and voltage conversion ratios. Finally, a 1.2-KW prototyped is built, and the simulation and the experimental results demonstrate that the power efficiency can be improved by using the optimization scheme based on the RL.