Optimal Distribution Strategy Research Articles

Electrified Powertrain with Multiple Planetary Gears and Corresponding Energy Management Strategy

Modern hybrid electric vehicles (HEVs) like the fourth generation of Toyota Prius incorporate multiple planetary gears (PG) to interconnect various power components. Previous studies reported that increasing the number of planetary gears from one to two reduces energy consumption. However, these studies did not compare one PG and two PGs topologies at their optimal operation. Moreover, the size of the powertrain components are not the same and hence the source of reduction in energy consumption is not clear. This paper investigates the effect of the number of planetary gears on energy consumption under optimal operation of the powertrain components. The powertrains with one and two PGs are considered and an optimal simultaneous torque distribution and mode selection strategy is proposed. The proposed energy management strategy (EMS) optimally distributes torque demands amongst the power components whilst also controlling clutches (i.e., mode selection). Results show that increasing from one to two PGs reduces energy consumption by 4%.

Research on Crushing Concrete Members by High-Voltage Pulse Discharge Technology

High-voltage pulse discharge (HVPD) is an energy-saving, efficient, and green technique, which has broad prospects in concrete crushing. The finite element models of the concrete beam, slab, and column segments were established with ANSYS/LS-DYNA finite element software. Based on the principle of equal impact pressure, the shock wave generated by the fuse explosion caused by HVPD of 50 kJ is equivalent to the impact load of explosive blasting, and the stress of concrete beam segment was analyzed. The finite element models of the concrete beam sections were established to investigate the influence of diameter and spacing of the holes on the crushing effect of concrete beam segments. The width × height of each beam segment is 400 mm × 800 mm, and there are six types of beam segment length: 600 mm, 700 mm, 800 mm, 900 mm, 1000 mm, and 1100 mm. Two holes are drilled vertically on the surface of the width × length of each beam segment. The spacing of holes corresponding to beam segments of each length type is 200 mm, 300 mm, 400 mm, 500 mm, 600 mm, and 700 mm, respectively. The hole depth of each beam segment is 650 mm, and there are three types of aperture: 30 mm, 50 mm, and 70 mm. The analysis results show that the crushing effect of concrete beam segments increases with the increase of aperture and the decrease of hole spacing. According to the crushing effect of the beam segments, the aperture of 50 mm, the spacing of 400 mm, and the hole end (edge) spacing of 250 mm were determined as the optimal hole layout scheme. The finite element models of concrete slabs and columns were established. The square concrete slab thickness is 140 mm and side length is 700 mm, 800 mm, and 900 mm, respectively. Double-row holes were arranged in the slabs and the aperture is 50 mm and the hole spacing is 200 mm, 300 mm, and 400 mm, respectively. The section sizes of concrete columns are 500 mm × 500 mm, 600 mm × 600 mm, and 700 mm × 700 mm, respectively, and the aperture is 50 mm and the hole distance is 400 mm. According to the results of analysis, the optimal hole distribution scheme of concrete slab and column is chosen as the aperture of 50 mm and hole distance of 400 mm. The principle of the layout of multirow holes is that the spacing of row is not more than 400 mm, and the margin is not more than 250 mm.

Energy management for hybrid energy storage system in electric vehicle: A cyber-physical system perspective

Adoption of the hybrid energy storage system (HESS) brings a bright perspective to improve the total economy of plug-in hybrid electric vehicles (PHEVs). This paper proposes a novel energy management method to improve the total economy of PHEV by exploiting the energy storage capability of HESS. Firstly, A cyber-physical energy management framework that enables the synergistic scheduling of fuel engine, battery, and supercapacitor is designed to derive the optimal power distribution strategy for PHEV with HESS. Then, an optimization-based energy management model is established to distribute the vehicle power requirement between the fuel engine and driving motor. The reduction of fuel cost and the mitigation of the battery aging phenomenon are designed as the optimization objectives. In a further stage, an online power distribution algorithm is designed for the optimal control of HESS, where the supercapacitor is used to prolong the battery life. The qualitative and quantitative analyses indicate that both the fuel economy and battery aging cost are sensitive to the power system topology and power distribution algorithm. With the proposed methods, the PHEV total economy can be improved by 8.9% and 6.9% compared to the conventional PHEV structure and power distribution strategy while guarantee the vehicle dynamic performance.

Substantial impact of post-vaccination contacts on cumulative infections during viral epidemics

Background: The start of 2021 was marked by the initiation of a global vaccination campaign against the novel coronavirus SARS-CoV-2. Formulating an optimal distribution strategy under social and economic constraints is challenging. Optimal distribution is additionally constrained by the potential emergence of vaccine resistance. Analogous to chronic low-dose antibiotic exposure, recently inoculated individuals who are not yet immune play an outsized role in the emergence of resistance. Classical epidemiological modelling is well suited to explore how the behavior of the inoculated population impacts the total number of infections over the entirety of an epidemic. Methods: A deterministic model of epidemic evolution is analyzed, with seven compartments defined by their relationship to the emergence of vaccine-resistant mutants and representing three susceptible populations, three infected populations, and one recovered population. This minimally computationally intensive design enables simulation of epidemics across a broad parameter space. The results are used to identify conditions minimizing the cumulative number of infections. Results: When an escape variant is only modestly less infectious than the originating strain within a naïve population, there exists an optimal rate of vaccine distribution. Exceeding this rate increases the cumulative number of infections due to vaccine escape. Analysis of the model also demonstrates that inoculated individuals play a major role in the mitigation or exacerbation of vaccine-resistant outbreaks. Modulating the rate of host–host contact for the inoculated population by less than an order of magnitude can alter the cumulative number of infections by more than 20%. Conclusions: Mathematical modeling shows that optimization of the vaccination rate and limiting post-vaccination contacts can perceptibly affect the course of an epidemic. The consideration of limitations on post-vaccination contacts remains relevant for the entire duration of any vaccination campaign including the current status of SARS-CoV-2 vaccination.

PREREQUISITES FOR THE FORMATION AND LOCALIZATION OF NARROW PLACES IN THE PRODUCT DISTRIBUTION SYSTEM

The key elements of logistics management of the distribution system of goods, in particular international trade networks, are studied. The parameters of evaluating the efficiency of individual distribution channels of goods in the distribution system are considered. The concept of "bottleneck" in the distribution network in general and individual distribution channels in particular has been clarified. The causes of bottlenecks in the distribution system channels, the points of localization of possible current restrictions - bottlenecks in the distribution system of goods are analyzed and the ways of their elimination are investigated. The results of research, methods and recommendations can be used to form the optimal distribution strategy of modern companies in conditions of unstable demand and under the influence of other negative factors. In view of the above, the task is to study in more detail the key elements of logistics procurement management for the defense sector in space and time and to develop practical recommendations for logistics management of the organization of defense procurement. Therefore, the aim of the study is to analyze the structure of the distribution network in conditions of unstable demand and under the influence of other negative factors in order to identify bottlenecks in the distribution system and find ways to eliminate them optimally.To achieve this goal, the following were investigated: priorities and guidelines for logistics management of the distribution system of goods from the manufacturer to the network of end users; structure and configuration of distribution channels in the distribution system as a subject of optimization; causes of bottlenecks in the distribution system channels and ways to eliminate them. Thus, logistics solutions localized in the field of distribution are a "trade-off" relationship with the sphere of production. That is, the field of distribution focuses on two important issues: first, the rationale and formation of distribution channels; secondly, the design and implementation of physical distribution of goods. In addition, the logistics management of the distribution system should be understood as the management of the process of moving goods from producer to end consumer, or their network, integrated with relevant financial, information and service flows to ensure a mix of logistics tasks.

On the Investigation of Energy Efficient Torque Distribution Strategies through a Comprehensive Powertrain Model

In electric vehicles with multiple motors, the torque at each wheel can be controlled independently, offering significant opportunities for enhancing vehicle dynamics behaviour and system efficiency. This paper investigates energy efficient torque distribution strategies for improving the operational efficiency of electric vehicles with multiple motors. The proposed strategies are based on the minimisation of power losses, considering the powertrain efficiency characteristics, and are easily implementable in real-time. A longitudinal dynamics vehicle model is developed in Simulink/Simscape environment, including energy models for the electrical machines, the converter, and the energy storage system. The energy efficient torque distribution strategies are compared with simple distribution schemes under different standardised driving cycles. The effect of the different strategies on the powertrain elements, such as the electric machine and the energy storage system, are analysed. Simulation results show that the optimal torque distribution strategies provide a reduction in energy consumption of up to 5.5% for the case-study vehicle compared to simple distribution strategies, also benefiting the battery state of charge.

Sequential Innovation and The Distribution of Profit: From Theory to Data

The distribution of profit is an essential problem for sequential innovation but still lacks related empirical research. By exploring a unique dataset from a game live streaming platform, we are among the first researchers to empirically measure the contribution of upstream and downstream innovators. From the perspective of the overall industry, the optimal distribution scheme is 1:1 for general streamers and game producers and 2:1 for professional streamers and game producers. This paper argues that the optimal distribution scheme between upstream and downstream innovators is based on their contribution share. The detailed distribution scheme also depends on streamer ability, game genres and the game's popularity.

All-Wheel-Drive Torque Distribution Strategy for Electric Vehicle Optimal Efficiency Considering Tire Slip

The existing energy management strategies for four-wheel-drive electric vehicles only take into account the vehicle energy consumption under static adhesion constraints. However, the front and rear axle loads transfer under dynamic conditions lead to the variations of vehicle adhesion characteristics, which results in the changes of vehicle energy consumptions. In this paper, a multi-objective optimal torque distribution strategy is proposed, taking into account the front and rear axle load transfer and the variations of adhesion characteristics. The advantages of the proposed strategy are verified through simulation studies in terms of vehicle energy consumption and wheel slip ratio, in comparison with the average torque distribution strategy and the optimal torque distribution strategy based on Sequential Quadratic Programming Algorithm. The simulation results show that the economy performance of the proposed strategy is superior to those of the competing methods. Furthermore, the proposed strategy provides good power performance and eliminates excessive wheel slip, which in turn ensures vehicle longitudinal stability and avoids energy loss resulting from frequent ASR interventions.

Lateral Stability Control of a 4-Wheel Independent Drive Electric Vehicle Using the Yaw Moment Contour Line Concept

This paper describes a new algorithm that independently manages braking and driving forces to improve the lateral stability of a vehicle equipped with independent drive motors on all wheels. In a similar way to previous research, the proposed algorithm controls yaw rate to improve lateral stability. However, unlike in previous research that only used differential braking, our algorithm controls both driving and braking forces on all four wheels independently to achieve the target yaw rate. The core contribution of this paper is the distribution logic that determines the braking and driving forces to apply at each wheel. To develop this distribution logic, we introduce the concept of yaw moment contour line. Using this concept, the optimal distribution strategy can be derived by considering yaw moment control performance, lateral movement performance, and deceleration minimization performance in eight different driving situations. Based on this strategy, we design a lateral stability control algorithm that is made up of a target yaw rate, a yaw moment controller, and a distributor. Simulations were performed to investigate the performance of the proposed algorithm using MATLAB/Simulink and the CarSim vehicle dynamics software. The simulation results show that the proposed control algorithm improves vehicle motion in terms of yaw rate tracking, lateral movement, and minimization of deceleration.

Edge Caching Strategy Based on User Preference and Game Theory

Caching video content to the mobile edge server is an effective solution to avoid multiple repeated requests from mobile terminal devices, reduce latency costs, and improve user QoE. In addition, mobile users in nearby areas tend to request the same video resource task, so reasonable deployment of video content to edge servers can effectively reduce the response time of user requests. This fact prompted us to design a caching strategy based on user preferences. The system model considered in this article contains multiple mobile users, multiple servers, and remote central servers. Based on the recommendation system predicting the user’s preference for specific video resources, the recommended value ranking of the video resources in the future time period is obtained, and then based on the game theory method, in each edge cache server, each video resource is calculated for the local area and neighboring areas. The cache value of the area, based on the cache value of the video resource to be cached, minimizes the delay for users to obtain the video resource, and obtains the optimal video resource cache distribution strategy. The simulation experiment results show that compared with other caching strategies, the proposed caching strategy is better than other caching strategies in terms of response time and cache task hit rate.

BigMPI4py: Python Module for Parallelization of Big Data Objects Discloses Germ Layer Specific DNA Demethylation Motifs.

Parallelization in Python integrates Message Passing Interface via the mpi4py module. Since mpi4py does not support parallelization of objects greater than 231 bytes, we developed BigMPI4py, a Python module that wraps mpi4py, supporting object sizes beyond this boundary. BigMPI4py automatically determines the optimal object distribution strategy, and uses vectorized methods, achieving higher parallelization efficiency. BigMPI4py facilitates the implementation of Python for Big Data applications in multicore workstations and High Performance Computer systems. We use BigMPI4py to speed-up the search for germ line specific de novo DNA methylated/unmethylated motifs from the 59 whole genome bisulfite sequencing DNA methylation samples from 27 human tissues of the ENCODE project. We developed a parallel implementation of the Kruskall-Wallis test to find CpGs with differential methylation across germ layers. The parallel evaluation of the significance of 55 million CpG achieved a 22x speedup with 25 cores allowing us an efficient identification of a set of hypermethylated genes in ectoderm and mesoderm-related tissues, and another set in endoderm-related tissues and finally, the discovery of germ layer specific DNA demethylation motifs. Our results point out that DNA methylation signal provide a higher degree of information for the demethylated state than for the methylated state. BigMPI4py is available at https://https://www.arauzolab.org/tools/bigmpi4py and https://gitlab.com/alexmascension/bigmpi4py and the Jupyter Notebook with WGBS analysis at https://gitlab.com/alexmascension/wgbs-analysis.

Cost-Effective App Data Distribution in Edge Computing

Edge computing, as an extension of cloud computing, distributes computing and storage resources from centralized cloud to distributed edge servers, to power a variety of applications demanding low latency, e.g., IoT services, virtual reality, real-time navigation, etc. From an app vendor's perspective, app data needs to be transferred from the cloud to specific edge servers in an area to serve the app users in the area. However, according to the pay-as-you-go business model, distributing a large amount of data from the cloud to edge servers can be expensive. The optimal data distribution strategy must minimize the cost incurred, which includes two major components, the cost of data transmission between the cloud to edge servers and the cost of data transmission between edge servers. In the meantime, the delay constraint must be fulfilled - the data distribution must not take too long. In this article, we make the first attempt to formulate this Edge Data Distribution (EDD) problem as a constrained optimization problem from the app vendor's perspective and prove its NP-hardness. We propose an optimal approach named EDD-IP to solve this problem exactly with the Integer Programming technique. Then, we propose an O(k)-approximation algorithm named EDD-A for finding approximate solutions to largescale EDD problems efficiently. EDD-IP and EDD-A are evaluated on a real-world dataset and the results demonstrate that they significantly outperform three representative approaches.

An adaptive coordinated optimal control method for parallel bidirectional power converters in AC/DC hybrid microgrid

Parallel bidirectional power converters (BPCs) play an important role in achieving mutual support between the two grids and in improving the power quality. One of the difficulties of the study is how to coordinated control BPCs to simultaneously realize the dual goals of economically distribute transmission power among BPCs and the high dynamic quality. In view of this, this paper proposes an adaptive coordinated optimal control method for the parallel BPCs. First, taking the minimization of the sum of the power losses of BPCs as the objective, the economically optimal distribution scheme for power transmission among parallel BPCs is calculated. Second, a primary voltage-regulated controller is designed, outer loop of the primary voltage-regulated controller can distribute the dynamic transmission power among BPCs according to the power margin of each BPC, to avoid overloading BPCs, and inner loop of the primary voltage-regulated controller can realize the decoupling of the output variable and the interference variable, to improve the dynamic voltage quality. Third, a secondary voltage-regulated controller is designed, it can make the dc bus voltage restore to the rated value quickly after power disturbance occurs, and ensure the economically optimal distribution of the transmission power among BPCs after the system reaches the steady state. Finally, the stability of the proposed control method is illustrated and conclusions are verified.

A Joint Optimization Strategy of Coverage Planning and Energy Scheduling for Wireless Rechargeable Sensor Networks

Wireless Sensor Networks (WSNs) have the characteristics of large-scale deployment, flexible networking, and many applications. They are important parts of wireless communication networks. However, due to limited energy supply, the development of WSNs is greatly restricted. Wireless rechargeable sensor networks (WRSNs) transform the distributed energy around the environment into usable electricity through energy collection technology. In this work, a two-phase scheme is proposed to improve the energy management efficiency for WRSNs. In the first phase, we designed an annulus virtual force based particle swarm optimization (AVFPSO) algorithm for area coverage. It adopts the multi-parameter joint optimization method to improve the efficiency of the algorithm. In the second phase, a queuing game-based energy supply (QGES) algorithm was designed. It converts energy supply and consumption into network service. By solving the game equilibrium of the model, the optimal energy distribution strategy can be obtained. The simulation results show that our scheme improves the efficiency of coverage and energy supply, and then extends the lifetime of WSN.

Continuous Damping Control for Rollover Prevention with Optimal Distribution Strategy of Damping Force

Vehicle rollover has always been a highly dangerous condition that can cause severe traffic casualties. In this work, a 14-degree-of-freedom vehicle model in MATLAB/Simulink is constructed with the vehicle suspension system dynamics. The validity of the model is verified by comparing with the CarSim model. Then an optimal distribution of damping force strategy with continuous damping control is proposed by combining the traditional lateral load transfer ratio control with optimized equations of suspension damping force. The damping force compensation of the left and right sides is the core of the optimal distribution of damping force strategy. The effectiveness and optimization effect of the optimal distribution of damping force strategy is proved by the simulation results under the fishhook and crosswind tests. The result shows that continuous damping control has evident control effects on vehicle rollover compared with passive suspension. The optimal distribution of the damping force strategy with continuous damping control has a great better performance than traditional continuous damping control, and it provides a certain assistance to vehicle handling stability.

Thermoeconomic analysis and inter‐stage pressure ratio optimization of nuclear power supercritical CO 2 multi‐stage recompression

Implemented optimization and full life cycle economic analysis on the inter-stage pressure ratio were rarely paid attention to in supercritical carbon dioxide multi-stage recompression. In this article, a thermodynamic model of supercritical carbon dioxide recompression Brayton cycle was established based on gas-cooled fast reactor and the sensitivity analysis was performed. With the aim of seeking the optimal pressure ratio for two-stage, three-stage, and four-stage recompression configuration, the full life cycle economic indicators were predicted, respectively. Parameter sensitivity analysis indicated that the thermodynamically optimized result could not coincide with that of the economically optimized. The optimal PR distribution scheme may result in the improvement of the initial cycle system efficiency from 46.89% to 48.07%. Meanwhile the levelized cost of electricity decreased from 57.40$/MWh to 55.87$/MWh. The approaching equilibrium trend of thermoeconomic parameters confirmed the existence of the optimal number of recompression stages, which could also be derived from the prediction tendency based on full life cycle economic indicators. Furthermore, it was discovered that reducing the year of repayment and the loan proportion enhanced the net present value of nuclear power plant, but the former method gave rise to longer payback period and lower internal rate of return. The present work preserves the guiding significance for nuclear power plant investors and the utilization of the supercritical carbon dioxide Brayton system.

Quality differentiation in a dual-channel supply chain

In this paper, we investigate a dual-channel supply chain with a retailer (she) and a manufacturer (he) who manufactures a high-quality product and a low-quality one. The manufacturer can distribute the high-quality and low-quality products in a direct channel (e.g., its own online channel) and an indirect channel (e.g., a traditional retailer channel) respectively, or the opposite. Our analyses reveal that the manufacturer's optimal distribution strategy depends on the product type. If the product's customer demand is more sensitive to quality level than production cost, it can be classified as the demand type. For a demand-type product, it is optimal for the manufacturer to sell its premium product through the direct channel to attract more demand. Otherwise, the product can be classified as the cost type and it is optimal for the manufacturer to sell its premium product through the traditional channel. In this way, the relatively high manufacturing cost can be shared with the retailer. Furthermore, we demonstrate the robustness of our results by analyzing an alternate demand model for the dual channels. Finally, we find that the manufacturer's optimal quality differentiation is detrimental to the retailer. Hence, we extend our basic model and show that the retailer can adopt an effective countermeasure by introducing an alternative supplier, even when the supplier charges a higher wholesale price.

DVRP with limited supply and variable neighborhood region in refined oil distribution

Limited supply can be an emergent issue in refined oil distribution, which may increase operating cost and decrease gasoline station satisfaction with shortage. Hence, how to devise an optimal distribution scheme is the central problem for oil distribution companies. The main problem with limited supply involves: (I) depicting the dynamic efforts on vehicle routing driven by the demand and priority of gasoline stations, and (II) incorporating the efforts into variable distribution region division associated with oil depots. In this paper, we propose a multi-objective optimization model for dynamic vehicle routing problem with limited supply in oil distribution with variable neighborhood region. First, a preliminary multi-stage model for dynamic vehicle routing problem is designed, which takes operating cost, gasoline station satisfaction and priority into consider in the setting of limited supply. Based on the preliminary model, a variable neighborhood region division model is presented for oil depot supply and tanker delivery, in light of Fuzzy C-means algorithm and justifiable granularity principle. Finally, the experimental results show that the dynamic vehicle programming model with variable neighborhood performs better than other comparable scenarios at cost savings and satisfaction improvement.

Multitasking scheduling with batch distribution and due date assignment

This study addresses the multitasking scheduling problems with batch distribution and due date assignment (DDA). Compared with classical scheduling problems with due date-related optimization functions, the job due dates are decision variables rather than given parameters. The jobs completed are distributed in batches, and the sizes of all batches are identical, which may be bounded or unbounded. The jobs in every batch are scheduled one by one. Each batch incurs a fixed cost. Under multitasking environment, it allows the machine to put an uncompleted job on hold and turn to another uncompleted job. The goal is to identify the optimal primary job sequence, the optimal job due dates, and the optimal batch production and distribution strategy so that one of the following two optimization functions is minimised: the total cost composed of the earliness penalty, DDA cost, tardiness penalty and batch distribution cost, and the total cost composed of the earliness penalty, weighted number of late jobs, DDA cost and batch distribution cost. We devise efficient exact algorithms for the problems we consider, and perform numerical experiments to check how multitasking affects the scheduling cost or value, the results of which can assist decision-makers to justify the extent to put to use or refrain from multitasking.

Nonlinear coordinated control of parallel bidirectional power converters in an AC/DC hybrid microgrid

Parallel bidirectional power converters (BPCs) can support each other's power between the ac grid and the dc grid, and they play an important role in maintaining the dynamic power balance in an ac/dc hybrid microgrid. This paper proposes a nonlinear coordinated control strategy for parallel BPCs when the hybrid ac/dc microgrid operates in grid-connected mode. First, taking the minimization of the sum of the power losses of the BPCs as the objective, this strategy can obtain the economically optimal distribution scheme for power transmission among parallel BPCs according to the efficiency curves of the BPCs. Second, distributing the transmission power according to the economically optimal distribution scheme rather than distributing the transmission power equally among parallel BPCs can not only reduce the sum of the power losses of the BPCs but also increase the power margin of the BPC that is used to control the dc bus voltage after a power disturbance. Third, a nonlinear control method that is based on the state-dynamic feedback linearization theory is proposed for the BPC that is used to control the dc bus voltage. This method can quickly re-establish the dc bus voltage if a power disturbance occurs and realize high dynamic voltage quality. Finally, the performance of the proposed control strategy is verified in MATLAB/Simulink.