混合动力汽车能效优化与控制策略研究

随着环境问题和能源危机的日益严重,混合动力汽车作为一种节能环保的交通工具,得到了广泛关注。能效优化和控制策略是混合动力汽车研究的重要方向,对于提高汽车性能、降低能耗、减少排放具有重要意义。本文旨在探讨混合动力汽车的能效优化和控制策略,以提高汽车的整体性能和燃油经济性。

Successful application of optimized aperture based CRS stack in the Shengli exploration area

The common reflection surface （CRS） stack is based on the local dip of the reflector and the reflection response within the first Fresnel zone. During the CRS stack all the information given by a multi-coverage reflection dataset can be successfully utilized. By now, it is known as the best zero-offset （ZO） imaging method. In this paper high quality CRS kinematic parameter sections are obtained by a modified CRS optimization strategy. Then stack apertures are calculated using the parameter sections which finally results in the realization of the CRS stack based on optimized aperture. Thus the advantages of CRS parameters are fully developed. Application to model and real seismic data reveals that, compared with the image section by a conventional CRS stack, the image section by CRS stack based on an optimized aperture improves both the signal-to-noise ratio and the continuity of reflection events.

A Geometric Process Repair Model for the Repairable System Consisting of One Component

This paper considers the optimal replacement problem of a repairable system consisting of one component and a single repairman, assume that the system after repair is not 'as good as new', by using the geometric process, we consider a placement policy T based on the age of the system. The problem is to determine the optimal replacement policy T * such that the long_run expected benefit per unit time is maximized. Also, the explicit expression of the long_run expected benefit per unit time can be found. In some conditions, the existence and uniqueness of the optimal policy T * can be proved, finally, we prove that the policy T * is better than the policy T * in .

Optimal quasi-periodic maintenance policies for two-unit series system

To investigate the effects of various random factors on the preventive maintenance （PM） decision-making of one type of two-unit series system, an optimal quasi-periodic PM policy is introduced. Assume that PM is perfect for unit 1 and only mechanical service for unit 2 in the model. PM activity is randomly performed according to a dynamic PM plan distributed in each implementation period. A replacement is determined based on the competing results of unplanned and planned replacements. The unplanned replacement is trigged by a catastrophic failure of unit 2, and the planned replacement is executed when the PM number reaches the threshold N. Through modeling and analysis, a solution algorithm for an optimal implementation period and the PM number is given, and optimal process and parametric sensitivity are provided by a numerical example. Results show that the implementation period should be decreased as soon as possible under the condition of meeting the needs of practice, which can increase mean operating time and decrease the long-run cost rate.

Multi-objective integrated optimization based on evolutionary strategy with a dynamic weighting schedule

The evolutionary strategy with a dynamic weighting schedule is proposed to find all the compromised solutions of the multi-objective integrated structure and control optimization problem, where the optimal system performance and control cost are defined by H2 or H∞ norms. During this optimization process, the weights are varying with the increasing generation instead of fixed values. The proposed strategy together with the linear matrix inequality （LMI） or the Riccati controller design method can find a series of uniformly distributed nondominated solutions in a single run. Therefore, this method can greatly reduce the computation intensity of the integrated optimization problem compared with the weight-based single objective genetic algorithm. Active automotive suspension is adopted as an example to illustrate the effectiveness of the proposed method.

The Development Status quo and Strategy of Aquatic Vegetables in Hunan

This paper reviews the development of aquatic vegetable production and research in Hunan. The advantages of aquatic vegetable industry in Hunan are discussed in detail on its location, brand, market, planting and processing. And the development strategies of the above-mentioned industry are further analyzed in the paper, such as variety resources, breeding and industrialization.

建筑外墙保温防火理论研究

本文通过分析火灾产生和蔓延的影响因素,建立了建筑外墙保温系统防火理论,提出了外墙外保温系统阻止火灾蔓延的边界条件,并给出了"微"、"分"、"优"三个防火策略,对于开发兼顾保温与防火、又满足75%以上建筑节能的新产品、新技术,提供了技术支撑。对提高现有保温系统的防火性能,消除建筑物使用过程中的火灾隐患具有现实指导意义。

Plan and Design of Landscapes as a Part of Construction of Beautiful Village

Construction of beautiful villages is an integral part of No.1 file issued by the central government and rural landscape planning plays an important role. The research reviewed the status quo of beautiful village construction, analyzed rural landscape planning and the optimized way for rural landscape planning, providing theoretical references for construction of beautiful village construction.

PCA weight and Johnson transformation based alarm threshold optimization in chemical processes

To alleviate the heavy load of massive alarm on operators, alarm threshold in chemical processes was optimized with principal component analysis(PCA) weight and Johnson transformation in this paper. First, few variables that have high PCA weight factors are chosen as key variables. Given a total alarm frequency to these variables initially, the allowed alarm number for each variable is determined according to their sampling time and weight factors. Their alarm threshold and then control limit percentage are determined successively. The control limit percentage of non-key variables is determined with 3σ method alternatively. Second, raw data are transformed into normal distribution data with Johnson function for all variables before updating their alarm thresholds via inverse transformation of obtained control limit percentage. Alarm thresholds are optimized by iterating this process until the calculated alarm frequency reaches standard level(normally one alarm per minute). Finally,variables and their alarm thresholds are visualized in parallel coordinate to depict their variation trends concisely and clearly. Case studies on a simulated industrial atmospheric-vacuum crude distillation demonstrate that the proposed alarm threshold optimization strategy can effectively reduce false alarm rate in chemical processes.

Application of new VBHF optimization strategy to improve formability of automobile panels with aluminum alloy sheet

A VBHF(Variable Blank Holder Force) optimization strategy was employed to determine the optimal time-variable and spatial-variable BHF trajectories,aiming at improving the formability of automobile panels with aluminum alloy sheet.The strategy was implemented based on adaptive simulation to calculate the critical wrinkling BHF for each segmented binder of the Numisheet' 05 deck lid in a single round of simulation.The thickness comparison of the stamped part under optimal VBHF and constant BHF shows that the variance of the four sections is decreased by 70%,44%,64% and 61%,respectively,which indicates significant improvement in thickness distribution and variation control.The investigation through strain path comparison reveals the fundamental reason of formability improvement.The study proves the applicability of the new VBHF optimization strategy to complex parts with aluminum alloy sheet.

Exact Solutions of VNE: A Survey

Network virtualization is an enabling technology of running multiple virtual networks on a shared substrate network. It aims to deal with the ossification of current network architecture. As a crucial component of network virtualization, virtual network embedding(VNE) can efficiently and effectively allocates the substrate resource to proposed virtual network requests. According to the optimization strategy, VNE approaches can be classified into three categories: exact, heuristic and meta-heuristic solution. The VNE exact solution is the foundation of its corresponding heuristic and meta-heuristic solutions. This paper presents a survey of existing typical VNE exact solutions, and open problems for the future research of VNE exact solutions are proposed.

ARX-NNPLS Model Based Optimization Strategy and Its Application in Polymer Grade Transition Process

Since it is often difficult to build differential algebraic equations (DAEs) for chemical processes, a new data-based modeling approach is proposed using ARX (AutoRegressive with eXogenous inputs) combined with neural network under partial least squares framework (ARX-NNPLS), in which less specific knowledge of the process is required but the input and output data. To represent the dynamic and nonlinear behavior of the process, the ARX combined with neural network is used in the partial least squares (PLS) inner model between input and output latent variables. In the proposed dynamic optimization strategy based on the ARX-NNPLS model, neither parameterization nor iterative solving process for DAEs is needed as the ARX-NNPLS model gives a proper representation for the dynamic behavior of the process, and the computing time is greatly reduced compared to conventional control vector parameterization method. To demonstrate the ARX-NNPLS model based optimization strategy, the polyethylene grade transition in gas phase fluidized-bed reactor is taken into account. The optimization results show that the final optimal trajectory of quality index determined by the new approach moves faster to the target values and the computing time is much less.

Multifunctional graphene‐based composite photocatalysts oriented by multifaced roles of graphene in photocatalysis

Graphene(GR),a single‐layer carbon sheet with a hexagonal packed lattice structure,has displayed attractive potential and demonstrably become the research focus in artificial photocatalysis due to its enchanting properties in enhancing light absorption,electron transfer dynamics,and surface reactions.Currently,numerous efforts have shown that the properties of GR,which are closely correlated to the photocatalytic performance of GR‐based composites are significantly affected by the synthesis methods.Herein,we first introduce the optimization strategies of GR‐based hybrids and then elaborate the synthesis of GR‐based composite photocatalysts oriented by manifold roles of GR in photoredox catalysis,containing photoelectron mediator and acceptor,improving adsorption capacity,regulating light absorption range and intensity,as well as macromolecular photosensitizer.Beyond that,a brief outlook on the challenges in this burgeoning research field and potential evolution strategies for enhancing the photoactivity of GR‐based hybrids is presented and we anticipate that this review could provide some enlightenments for the rational construction and application of multifunctional GR‐based composite photocatalysts.

An Optimal Control Strategy Combining SVM with RGA for Improving Fermentation Titer

An optimal control strategy is proposed to improve the fermentation titer,which combines the support vector machine(SVM)with real code genetic algorithm(RGA).A prediction model is established with SVM for penicillin fermentation processes,and it is used in RGA for fitting function.A control pattern is proposed to overcome the coupling problem of fermentation parameters,which describes the overall production condition.Experimental results show that the optimal control strategy improves the penicillin titer of the fermentation process by 22.88%,compared with the routine operation.

Hybrid Strategy of Particle Swarm Optimization and Simulated Annealing for Optimizing Orthomorphisms

Orthomorphism on F2^n is a kind of elementary pemmtation with good cryptographic properties. This paper proposes a hybrid strategy of Particle Swarm Optimization （PSO） and Sirrmlated Annealing （SA） for finding orthomorphisrm with good cryptographic properties. By experiment based on this strategy, we get some orthorrorphisrm on F2^n = 5, 6, 7, 9, 10） with good cryptographic properties in the open document for the first time, and the optirml orthorrrphism on F found in this paper also does better than the one proposed by Feng Dengguo et al. in stream cipher Loiss in difference uniformity, algebraic degree, algebraic irrarnity and corresponding pernmtation polynomial degree. The PSOSA hybrid strategy for optimizing orthomerphism in this paper makes design of orthorrorphisrm with good cryptographic properties automated, efficient and convenient, which proposes a new approach to design orthornorphisrm.

Response Surface Optimization for Process Parameters of LiFePO_4/C Preparation by Carbothermal Reduction Technology

A statistically based optimization strategy is used to optimize the carbothermal reduction technology for the synthesis of LiFePO4/C using LiOH,FePO4 and sucrose as raw materials.The experimental data for fitting the response are collected by the central composite rotatable design(CCD).A second order model for the discharge ca-pacity of LiFePO4/C is expressed as a function of sintering temperature,sintering time and carbon content.The ef-fects of individual variables and their interactions are studied by a statistical analysis(ANOVA).The results show that the linear effects and the quadratic effects of sintering temperature,carbon content and the interactions among these variables are statistically significant,while those effects of sintering time are insignificant.Response surface plots for spatial representation of the model illustrate that the discharge capacity depends on sintering temperature and carbon content more than sintering time.The model obtained gives the optimized reaction parameters of sinter-ing temperature at 652.0 ℃,carbon content of 34.33 g?mol-1 and 8.48 h sintering time,corresponding to a dis-charge capacity of 150.8 mA·h·g-1.The confirmatory test with these optimum parameters gives the discharge ca-pacity of 147.2 and 105.1 mA·h·g-1 at 0.5 and 5 C,respectively.

Optimum control strategy for all-variable speed chiller plant

The optimum control strategy and the saving potential of all variable chiller plant under the conditions of changing building cooling load and cooling water supply temperature were investigated. Based on a simulation model of water source chiller plant established in dynamic transient simulation program (TRNSYS),the four-variable quadratic orthogonal regression experiments were carried out by taking cooling load,cooling water supply temperature,cooling water flow rate and chilled water flow rate as variables,and the fitting formulas expressing the relationships between the total energy consumption of chiller plant with the four selected parameters was obtained. With the SAS statistical software and MATHEMATICA mathematical software,the optimal chilled water flow rate and cooling water flow rate which result in the minimum total energy consumption were determined under continuously varying cooling load and cooling water supply temperature. With regard to a chiller plant serving an office building in Shanghai,the total energy consumptions under different control strategies were computed in terms of the forecasting function of cooling load and water source temperature. The results show that applying the optimal control strategy to the chiller plant can bring a saving of 23.27% in power compared with the corresponding conventional variable speed plant,indicating that the optimal control strategy can improve the energy efficiency of chiller plant.

Optimal restructuring strategies under various dynamic factors

Corporate restructuring was identified as a new industrial force that has great impact on economic values and that therefore has become central in daily financial decision making. This article investigates the optimal restructuring strategies under different dynamic factors and their numerous impacts on firm value. The concept of quasi-leverage is introduced and valuation models are built for corporate debt and equity under imperfect market conditions. The model’s input variables include the quasi-leverage and other firm-specific parameters, the output variables include multiple corporate security values. The restruc- turing cost is formulated in the form of exponential function, which allows us to observe the sensitivity of the variation in security values. The unified model and its analytical solution developed in this research allow us to examine the continuous changes of security values by dynamically changing the coupon rates, riskless interest rate, bankruptcy cost, quasi-leverage, personal tax rate, corporate taxes rate, transaction cost, firm risk, etc., so that the solutions provide useful guidance for financing and restructuring decisions.

Design of Underwater Robot Lines Based on a Hybrid Automatic Optimization Strategy

In this paper, a hybrid automatic optimization strategy is proposed for the design of underwater robot lines. Isight is introduced as an integration platform. The construction of this platform is based on the user programming and several commercial software including UG6.0, GAMBIT2.4.6 and FLUENT12.0. An intelligent parameter optimization method, the particle swarm optimization, is incorporated into the platform. To verify the strategy proposed, a simulation is conducted on the underwater robot model 5470, which originates from the DTRC SUBOFF project. With the automatic optimization platform, the minimal resistance is taken as the optimization goal;the wet surface area as the constraint condition; the length of the fore-body, maximum body radius and after-body＇s minimum radius as the design variables. With the CFD calculation, the RANS equations and the standard turbulence model are used for direct numerical simulation. By analyses of the simulation results, it is concluded that the platform is of high efficiency and feasibility. Through the platform, a variety of schemes for the design of the lines are generated and the optimal solution is achieved. The combination of the intelligent optimization algorithm and the numerical simulation ensures a global optimal solution and improves the efficiency of the searching solutions.

Hybrid optimization model and its application in prediction of gas emission

According to the complex nonlinear relationship between gas emission and its effect factors, and the shortcomings that basic colony algorithm is slow, prone to early maturity and stagnation during the search, we introduced a hybrid optimization strategy into a max-rain ant colony algorithm, then use this improved ant colony algorithm to estimate the scope of RBF network parameters. According to the amount of pheromone of discrete points, the authors obtained from the interval of net- work parameters, ants optimize network parameters. Finally, local spatial expansion is introduced to get further optimization of the network. Therefore, we obtain a better time efficiency and solution efficiency optimization model called hybrid improved max-min ant system （H1-MMAS）. Simulation experiments, using these theory to predict the gas emission from the working face, show that the proposed method have high prediction feasibility and it is an effective method to predict gas emission.