Power Splitting Architecture Research Articles

Joint Beam-Forming Optimization for Active-RIS-Assisted Internet-of-Things Networks with SWIPT

Network energy resources are limited in communication systems, which may cause energy shortages in mobile devices at the user end. Active Reconfigurable Intelligent Surfaces (A-RIS) not only have phase modulation properties but also enhance the signal strength; thus, they are expected to solve the energy shortage problem experience at the user end in 6G communications. In this paper, a resource allocation algorithm for maximizing the sum of harvested energy is proposed for an active RIS-assisted Simultaneous Wireless Information and Power Transfer (SWIPT) system to solve the problem of low performance of harvested energy for users due to multiplicative fading. First, in the active RIS-assisted SWIPT system using a power splitting architecture to achieve information and energy co-transmission, the joint resource allocation problem is constructed with the objective function of maximizing the sum of the collected energy of all users, under the constraints of signal-to-noise ratio, active RIS and base station transmit power, and power splitting factors. Second, the considered non-convex problem can be turned into a standard convex problem by using alternating optimization, semi-definite relaxation, successive convex approximation, penalty function, etc., and then an alternating iterative algorithm for harvesting energy is proposed. The proposed algorithm splits the problem into two sub-problems and then performs iterative optimization separately, and then the whole is alternately optimized to obtain the optimal solution. Simulation results show that the proposed algorithm improves the performance by 45.2% and 103.7% compared to the passive RIS algorithm and the traditional without-RIS algorithm, respectively, at the maximum permissible transmitting power of 45 dBm at the base station.

Energy enhancement and efficient route selection mechanism using H-SWIPT for multi-hop IoT networks

Simultaneous wireless information and power transfer (SWIPT) is recently emerging as one of the vital solutions to prolong the lifetime of energy constrained wireless sensor nodes. However, current works on SWIPT considered only the immediate past-hop node's RF signal as a source of energy harvesting in multi-hop Internet of things (IoT) networks. In case of weak radio frequency (RF) signal, the amount of harvested energy does not support for continuous communication. Hence, in this paper a new energy harvesting mechanism is proposed which considers multiple sources (MS) such as (1) sink broadcasting energy, (2) co-channel interference, (3) neighbor nodes' RF signal, and (4) immediate past-hop node's RF signal for energy harvesting. Towards such prospect, a new SWIPT architecture is proposed called hybrid SWIPT (H-SWIPT) by integrating time switching (TS) and power splitting (PS) architectures. Furthermore, an efficient route selection mechanism is introduced to minimize the total energy consumption of the path based on an energy cost metric. To validate the proposed mechanism, simulation experiments are conducted and obtained the superiority of H-SWIPT compared with existing methods in terms of average harvested energy. Further, the effectiveness of proposed method performance is investigated through energy cost at different node density and barrier rates.

Numerical Performance Investigation of a Hybrid eCVT Specialized Agricultural Tractor

The need for highly efficient agricultural machineries is increasing the interest of the research community and of industrial manufacturers towards the use of integrated electric systems in combination with traditional powertrain elements. In this work, a hybrid electric tractor with electric continuously variable transmission (eCVT) capabilities was studied to investigate their performance in comparison with that of traditional diesel-powered tractor designs. This hybrid electric configuration can be classified as a power-split architecture that aims to combine the best characteristics of both the simpler parallel and the series hybrid layout while minimizing their main drawbacks. An eCVT configuration can allow for optimizing the diesel operating point with respect to the current working conditions, and achieving peak power performance and energy saving with relatively small electric machines. The proposed hybrid eCVT (HeCVT) tractor architecture was studied using a numerical model that allowed for developing two different control strategies: a charge depleting mode enabling the driver to use full power for the most power-intensive scenarios and a charge sustaining mode developed to optimize efficiency and battery use along an entire work day. To test the proposed architecture, several tasks derived from experimental field measurements on a specialized agricultural tractor were used. HeCVT results were compared with a numerical model of the traditional tractor validated by these experimental data. The HeCVT tractor showed good performance in terms of peak power capabilities using a downsized diesel engine, and consistent fuel savings were obtained according to typical daily working scenarios.

Power Losses Minimization for Optimal Operating Maps in Power-Split HEVs: A Case Study on the Chevrolet Volt

The power-split architecture is the most promising hybrid electric powertrain. However, a real advantage in energy saving while maintaining high performance can be achieved only by the implementation of a proper energy management strategy. This requires an optimized functional design before and a comprehensive analysis of the powertrain losses after, which could be rather challenging owing to the constructive complexity of the power-split transmission, especially for multi-mode architecture with multiple planetary gearing. This difficulty was overcome by a dimensionless model, already available in the literature, that enables the analysis of any power-split transmission, even in full electric operation. This paper relies on this approach to find the operating points of the internal combustion engine and both electric machines which minimize the total power losses. This optimization is carried out for given vehicle speed and demanded torque, by supposing different scenarios in respect of the battery capability of providing or gathering power. The efficiency of the thermal engine and the electric machines is considered, as well as the transmission mechanical power losses. The aim is to provide a global efficiency map that can be exploited to extract data for the implementation of the most suitable real-time control strategy. As a case study, the procedure is applied to the multi-mode power-split system of the Chevrolet Volt.

Impact of the hybrid electric architecture on the performance and emissions of a delivery truck with a dual-fuel RCCI engine

Reactivity controlled compression ignition combustion showed great advantages in terms of NOx and soot emissions reduction, leading to virtually zero emissions. However, the average brake thermal efficiency of this concept is like that found with conventional diesel operation. The powertrain electrification using electric motors and battery packages appears as a potential solution to reduce the CO2 emissions. For this reason, several solutions for the powertrain electrification can be found currently in the market as the parallel, series and power split powertrain architectures. The aim of this work is to evaluate the hybrid architecture impact on the fuel consumption and emissions of a delivery truck (Volvo-FL) intended for urban and urban–rural applications. The truck equipped with a reactivity-controlled compression ignition diesel-gasoline engine is evaluated and compared against the conventional diesel case. In addition, to evaluate the impact of new e-fuels on the well-to-wheel CO2 emissions, a synthetic gasoline coming from carbon capture and green electricity is evaluated. The results show that hybridization allows reducing the tank-to-wheel CO2 emissions above 15% with the parallel hybrid set-up. The series and power split architectures show CO2 benefits of 12% with respect to the baseline diesel non-hybrid case. Using synthetic gasoline as low reactivity fuel allows to achieve a 50% well-to-wheel CO2 reduction in the P2 and 70% well-to-wheel CO2 reduction for the series and power split cases due to the higher average gasoline fraction used in the driving cycle.

A design approach for multi-configuration hybrid transmission mechanisms

Several hybrid architectures have been widely used in hybrid electric vehicles. For example, power-split architecture brings seamless operation, while parallel architecture makes the internal combustion engine directly drive the wheel. To combine the advantages of various architectures, this study aims to develop a design approach to create a transmission mechanism that has multiple configurations and uses these configurations to achieve several hybrid architectures. First, this study standardized hybrid transmission mechanisms using the Function Power Graph; this powerful and intuitive tool inspired several elements and an element layout for the new mechanisms. Then, several configurations with up to five elements were enumerated and organized into the databases. Next, the mechanisms with multiple configurations and a limited number of clutching units (clutches or brakes) were evaluated, 10 of which were identified as the best group that provided five parallel configurations, two 2-motor electric vehicle configurations, and a power-split configuration. At the end of this paper, a novel hybrid transmission mechanism was developed as a demonstration. It provides higher power and torque at the output but there is no need to use the larger internal combustion engine or motor-generators. This mechanism also enables the internal combustion engine to drive in overdrive parallel architectures to avoid the loss in energy conversion when the power-split architecture is not required. As a result, after a designer specifies the desired hybrid configurations, follows the procedure, and uses the configuration databases built in this study, a novel hybrid transmission mechanism will be created.

Impartial SWIPT-Assisted User Cooperation Schemes

In this paper, an impartial simultaneous wireless information and power transfer (SWIPT)-assisted cooperation mechanism is proposed for a non-orthogonal multiple access (NOMA) downlink scenario. The key idea of the proposed impartial user cooperation mechanism (IUCM) is that not only the cell-center user but also the cell-edge user applies the power-splitting architecture and utilizes the harvested energy to forward the other user's information. Analytical results show that the proposed IUCM outperforms the traditional partial cooperation mechanism in terms of outage probability, diversity order and diversity-multiplexing trade-off (DMT). For comparison, the proposed IUCM is further incorporated into an orthogonal frequency-division multiple access (OFDMA) framework, which is shown to preserve the same diversity order, while has a worse but more flexible DMT performance compared with the IUCM in the NOMA framework. Furthermore, a classic non-linear energy harvesting model is introduced, based on which the outage probability, diversity order and DMT performance of the proposed IUCM and the conventional mechanism are analyzed. Finally, representative numerical results are given to validate our theoretical analysis.

Resource allocation of simultaneous wireless information and power transmission of multi-beam solar power satellites in space–terrestrial integrated networks for 6G wireless systems

The technique of simultaneous wireless information and power transmission (SWIPT) has been applied to wireless sensor networks, which employ static or mobile base stations (BSs) such as drones and ships to charge passively powered devices. SWIPT can be strongly expanded by solar power satellites (SPSs), which collect solar energy and transmit it to the earth through microwaves to alleviate the power shortage problem. Furthermore, multi-beam SPSs can serve a broader range than terrestrial BSs for information transmission.In 6G networks, satellites are core devices in space-terrestrial integrated networks (STINs) supporting super Internet-of-Things. However, when discussing 6G wireless systems, previous works did not consider SWIPT applied in STINs through multi-beam SPSs. Therefore, this work proposes a novel resource allocation problem for SWIPT performed by multi-beam SPSs in the STIN while optimizing the following two objectives: minimizing deficit or excess of information transmission rate and maximizing power transmission based on two receiving architectures of terrestrial devices for information decoding and energy harvesting. Different from previous works, this problem considers not only assigning power to one of multiple satellite beams but also further allocating power in each beam into two parts for information and power transmission. This problem is NP-hard as it includes an NP-hard problem. Artificial intelligence (AI) algorithms can be used to optimize the network resource management. Hence, this problem with continuous decision variables is further solved by a classical and two recent AI algorithms specially designed for continuous variables, i.e., particle swarm optimization, improved harmony search algorithm, and monkey algorithm. Through simulation, the most appropriate AI algorithms to the concerned problem are analyzed, and the results show that for the two special designed receiving architectures of the terrestrial devices, the power splitting architecture generally outperforms the time switching architecture.

Energy-Efficient SWIPT-Empowered D2D Mode Selection

While mode selection has been envisioned as the most cost-effective way to address the interference issue in Device-to-Device (D2D) communications, existing works have been largely conducted without consideration of the energy depletion of devices. In this paper we investigate simultaneous wireless information and power transfer (SWIPT) empowered mode selection based on stochastic geometry. As a mean of solving it, system energy efficiency is formulated by determining the closed-form ergodic energy-harvested and ergodic capacity of D2D and cellular users in reuse, dedicated, and cellular communication modes with the time switching and power splitting architectures of SWIPT. We then leverage the derived results, along with the energy efficiency to design an energy-efficient mode selection mechanism. Our simulation results show that the developed mechanism is able to select the best mode for D2D communication with better energy efficiency, especially in an ultra-dense cellular network as compared with a state-of-the-art mode selection approach.

Power Allocation for D2D Communications With SWIPT

Power allocation plays a vital role in coordinating interference between Device-to-Device (D2D) and cellular communications, and when power allocation meets simultaneous wireless information and power transfer (SWIPT), the energy efficiency of D2D communications can be significantly improved. While numerous research studies have been conducted on D2D power allocation, most of these studies do not take the presence of SWIPT into consideration. Toward a remedy for this issue, we investigate the problem of D2D power allocation with SWIPT power-splitting architecture, and address it by establishing a novel game-theoretic model. Two power allocation mechanisms are proposed to simultaneously allocate transmit power and choose power splitting ratio for D2D communications. We also develop two pricing strategies for the proposed power allocation mechanisms based on the social utility (sum utility of both D2D and cellular communications) maximization. Simulation results validate theoretical analyses and the effectiveness of the proposed mechanisms. In particular, we find through performance comparisons that our developed pricing strategies are light-weighted and energy-efficient, and the distributed power allocation mechanism is responsive to the mobility of D2D users.

Secrecy outage analysis of a NOMA EH network with backhaul connections

In this paper, we investigate the secrecy performance of a non-orthogonal multiple access system (NOMA) using imperfect successive interference cancellation (SIC) in a multiple untrusted energy harvesting (EH) relaying network with unreliable backhaul links. The best transmitter (Tx) and untrusted relay are selected to assist communication between the base station (BS) and destination users. Moreover, the best untrusted relay using the amplify-and-forward (AF) protocol and the power-splitting (PS) architecture works as both a helper that assists in forwarding the received signals from the Tx to destination users and as an eavesdropper that tries to overhear the confidential information. To enhance the secrecy capacity and protect the confidential source data from overhearing of an untrusted relay, the BS sends artificial noise (AN) or jamming signals. Furthermore, in this paper, we consider the imperfect cancelation of the jamming signal at the destination users. To evaluate the secrecy outage performance of users and the overall system, we derive closed-form expressions of the secrecy outage probability (SOP) under Rayleigh fading channels. We also use Monte Carlo simulations to verify the accuracy of the analytical results. The SOP comparison between NOMA and OFDM systems and the influence of various system parameters are analyzed to obtain valuable insights about both systems.

Representation, generation, and optimization methodology of hybrid electric vehicle powertrain architectures

Since the first commercial application of hybrid electric vehicle (HEV) powertrains, power-split architectures have been a major option for construction of HEV powertrains. Are power-split HEV powertrains the best solution to all design-objective settings, or will other design schemes arise that better fit the design requirements? To generalize the system optimization to different types of HEV powertrains, representation and generation methods for generic architectures of HEV powertrain are developed, which completely clarify the available design domain of the HEV powertrain architecture. Then, an integrated multi-objective optimization that simultaneously optimizes the architecture, component parameters, and control strategy is engineered to obtain the Pareto optimal design schemes of HEV powertrains in various situations of trade-off between acceleration capacity and fuel economy. The results suggest that the power-split HEV powertrain is superior in fuel economy and the HEV powertrain adopting the architecture with torque coupling among the engine and motor/generators (1-1 type) is superior in acceleration capacity. However, the achievable optimal fuel economies of power-split and 1-1 type HEV powertrains are almost the same, whereas the trade-off ranges of power-split HEV powertrains are narrower than those of the 1-1 type architecture HEV powertrains. Conceptually, the results reflect that when design methods are restricted to a specific subspace of the design domain, due to the limited consideration of variation in HEV powertrain architectures, the theoretical optimality of the design is not guaranteed. Practically, 1-1 type architecture can be more adaptive to different trade-offs among design objectives. For variations in design objectives, the appropriate HEV powertrain can be constructed by modifying in component parameters of the 1-1 No. 5 architecture HEV powertrain rather than reconstruction of the powertrain with architectural modifications.

Efficiency Improvement of a Series–Parallel Hybrid Electric Powertrain by Topology Modification

Among Series-Parallel Hybrid Electric Vehicle (SPHEV) powertrains, the Power-Split architecture with a planetary gear has an exemplary energetic efficiency in mixed driving conditions. Nevertheless, a simple SPHEV architecture can be realized without a planetary gear. It consists of 2 Electric Machines (EM) mounted on the engine shaft and separated by a clutch. With no power-split operation, this architecture allows the vehicle to operate in pure electric, or series hybrid, or parallel hybrid mode. It was proven to be less efficient than a reference Power-Split SPHEV: the Toyota Hybrid System (THS). The aim of this paper is to investigate the potential of efficiency improvement of the simple SPHEV powertrain by topology modification: the addition of gears for the components or a gearbox with few number of ratios. Two new variants of SPHEVs are proposed. The versions of SPHEVs and the reference THS are optimized by a bi-level optimization technique using Genetic Algorithm and Dynamic Programming. Compared to the simple SPHEV, results show an efficiency worsening in one variant and an efficiency improvement in another variant with a fuel consumption comparable to the one of THS. A global sensitivity study is then performed on the worsened variant. The sensitivities of the added gears are determined and an elimination of some is suggested. A new variant with fewer gears is therefore proposed and optimized. The efficiency is improved but remains less than the one of THS.

Distributed ADMM-based approach for total harvested power maximization in non-linear SWIPT system

In this paper, the distributed alternating direction method of multipliers (ADMM)-based approach is investigated for total harvested power maximization (THPM) in multiple-input single-output transceiver pairs with simultaneous wireless information and power transfer. The power-splitting architecture and practical non-linear energy harvesting are utilized at each receiver. The highly non-convex THPM problem is formulated under requirements for the data rate, the amount of harvested power, and with limited power at the transmitters. First, semidefinite relaxation (SDR) and sequential parametric convex approximation are exploited to convert the non-convex THPM to a series of convex subproblems. Then, slack variables replacing interference are introduced to allow decomposing into distributed subproblems via ADMM. The interesting point is that optimal precoding matrices of the local subproblems satisfy the rank-1 constraints of SDR. Finally, the numerical experiments present the convergence of the proposed algorithm, obtaining results similar to the centralized approach, as well as comparing it with some baseline schemes.

Optimization issues for data rate in energy harvesting relay-enabled cognitive sensor networks

This paper looks into an energy harvesting (EH) relay-enabled cognitive radio wireless sensor network (CR-WSN) considering power splitting (PS) architecture. More specifically, a relay (RU) harvesting energy from the signals transmitted from a secondary user transmitter (ST,) and using the harvested energy to forward the resulting signals to another sensor node subsequently is being investigated. This scheme can be broken down into two components, i.e., a sensor node physically placed near the transmitter (SPNT) and a sensor node physically placed far from the transmitter (SPFT). The closed-form expressions for the successful transmission probability (STP) and the achievable data rate in both cases can be derived analytically. In order to quantify the energy consumption, the system energy efficiency (EE) is examined. Furthermore, the achievable data rate was optimized in three possible scenarios, i.e., the trade-off between the sum data rate and the sum harvested energy (R-E), the achievable data rate at RU, and the joint optimization of the power allocation and PS ratio in case of SPNT. A Monte Carlo simulation has been performed to verify the theoretical analysis obtained, and to show the impact of different parameters on system performance.

Integration of On-Line Control in Optimal Design of Multimode Power-Split Hybrid Electric Vehicle Powertrains

The multimode power-split architecture for hybrid electric vehicle (HEV) powertrains is generally known for the complexity of its operation. This paper first addresses the challenge of developing an automated on-line near-optimal control strategy for these systems. Particularly, a machine learning logic based on supervised learning is developed for on-line selection of the HEV operating mode, thus the particular set of clutches to be engaged. An efficiency-based approach is then adopted to determine the optimal power-split between powertrain components. Later, the developed strategy finds integration in an optimal design methodology for multimode power-split HEVs considering the effectiveness and ease of on-line controllability. The obtained results are compared with the ones by the traditional HEV design methodology that only considers off-line energy management. The illustrated design methodology with on-line control reveals efficient at identifying the multimode HEV design that demonstrates optimal predicted fuel economy values and ease of on-line controllability simultaneously. Results suggest that the HEV design optimization procedure may produce different outcomes and demonstrate more effective when the evaluation of the on-line controlled operation is integrated.

Robust Beamforming Design in a NOMA Cognitive Radio Network Relying on SWIPT

This paper studies a multiple-input single-output non-orthogonal multiple access cognitive radio network relying on simultaneous wireless information and power transfer. A realistic non-linear energy harvesting model is applied and a power splitting architecture is adopted at each secondary user (SU). Since it is difficult to obtain perfect channel state information (CSI) in practice, instead either a bounded or Gaussian CSI error model is considered. Our robust beamforming and power splitting ratio are jointly designed for two problems with different objectives, namely, that of minimizing the transmission power of the cognitive base station and that of maximizing the total harvested energy of the SUs, respectively. The optimization problems are challenging to solve, mainly because of the non-linear structure of the energy harvesting and CSI errors models. We converted them into convex forms by using semi-definite relaxation. For the minimum transmission power problem, we obtain the rank-2 solution under the bounded CSI error model, while for the maximum energy harvesting problem, a two-loop procedure using a 1-D search is proposed. Our simulation results show that the proposed scheme significantly outperforms its traditional orthogonal multiple access counterpart. Furthermore, the performance using the Gaussian CSI error model is generally better than that using the bounded CSI error model.

Energy Efficiency Maximization Design for Full-Duplex Cooperative NOMA Systems With SWIPT

This paper investigates non-orthogonal multiple access (NOMA) system, where the near NOMA user is able to communicate with a base station (BS) directly while the far NOMA user needs to resort to a full-duplex (FD) relay. Wireless power transfer is applied to our system where the FD relay integrated with power splitting architecture can be powered wirelessly by the ambient radio signals simultaneously. Moreover, we assume that self-interference cancellation at the relay and inter-user interference cancellation at the near NOMA user are imperfect. For the purpose of maximizing the energy efficiency of the NOMA system, the power splitting ratio and transmit beamforming vectors are researched for the BS and relay with the guarantee of QoS requirements for two users. The formulated problem appears to be nonlinear fractional programming, which is highly nonconvex and the global optimality is hard to obtain. By introducing Charnes-Cooper's transformation and inner approximation method, we develop an iterative algorithm to gain the near optimal solution. The simulation results show that the proposed joint optimizing algorithm outperforms the existing scheme in terms of energy efficiency as well as the effect of SI cancellation on performance gain.

Transceiver Design for Downlink SWIPT NOMA Systems With Cooperative Full-Duplex Relaying

This paper studies the application of simultaneous wireless information and power transfer (SWIPT) to downlink non-orthogonal multiple access (NOMA) system. A novel cooperative NOMA protocol for high communication reliability and user fairness is proposed, where a near NOMA user acts as a full-duplex (FD) energy-harvesting relay to help transmission from the source node S to the far NOMA user. The power splitting (PS) architecture is adopted at the relay to perform the SWIPT. The aim is to maximize the data rate of the near NOMA user while satisfying the QoS requirement of the far NOMA user and the energy causality condition of the near NOMA user. The formulated problem is a non-convex fractional programming. By jointly optimizing the power allocation factor, the PS ratio, the receiver filter, and the transmit beamforming, we propose alternative optimization (AO)-based algorithm to obtain an optimal solution. In addition, a low-complexity suboptimal scheme is proposed and the semi-closed form solution is derived to characterize the performance of our proposed design. The simulation results verify the correctness of theoretical analysis and show performance gain of our proposed protocol over the existing transmission protocols.

Energy efficiency optimization for SWIPT in K-user MIMO interference channels

In this paper, we investigate the energy efficiency (EE) for K-user multiple-input multiple-output (MIMO) interference channels with simultaneous wireless information and power transfer (SWIPT) and interference alignment (IA). Specifically, power splitting architecture is leveraged at each receiver for information decoding (ID) and energy harvesting simultaneously. Taking the quality of service (Qos) requirement and harvested power constraints into consideration, we maximize the system EE by jointly designing transmit beamformers, transmit power, power splitters and receive filters. To solve the nonconvex EE optimization problem, we first eliminate the interference among users for ID via the maximal signal to interference plus noise ratio (Max-SINR) IA method, which yields a two-dimensional EE optimization problem. And then, we propose an EE-Max algorithm coupled with the Max-SINR, nonlinear fraction programming and one dimension searching to solve the reformulated problem. Simulation results show the effectiveness of the proposed EE optimization algorithm and reveal the influence of the maximum transmit power constraint and the QoS requirement on the system EE.