Optimal Design of the Modular Joint Drive Train for Enhancing Cobot Load Capacity and Dynamic Performance

Automation advancements prompts the extensive integration of collaborative robot(cobot)across a range of industries.Compared to the commonly used design approach of increasing the payload-to-weight ratio of cobot to enhance load capacity,equal attention should be paid to the dynamic response characteristics of cobot during the design process to make the cobot more flexible.In this paper,a new method for designing the drive train parameters of cobot is proposed.Firstly,based on the analysis of factors influencing the load capacity and dynamic response characteristics,design criteria for both aspects are established for cobot with all optimization design criteria normalized within the design domain.Secondly,with the cobot in the horizontal pose,the motor design scheme is discretized and it takes the joint motor diameter and gearbox speed ratio as optimization design variables.Finally,all the discrete values of the optimization objectives are obtained through the enumeration method and the Pareto front is used to select the optimal solution through multi-objective optimization.Base on the cobot design method proposed in this paper,a six-axis cobot is designed and compared with the commercial cobot.The result shows that the load capacity of the designed cobot in this paper reaches 8.4 kg,surpassing the 5 kg load capacity commercial cobot which is used as a benchmark.The minimum resonance frequency of the joints is 42.70 Hz.

A Multiscale Reliability-Based Design Optimization Method for Carbon-Fiber-Reinforced Composite Drive Shafts

Carbon fiber composites,characterized by their high specific strength and low weight,are becoming increasingly crucial in automotive lightweighting.However,current research primarily emphasizes layer count and orientation,often neglecting the potential of microstructural design,constraints in the layup process,and performance reliability.This study,therefore,introduces a multiscale reliability-based design optimization method for carbon fiber-reinforced plastic(CFRP)drive shafts.Initially,parametric modeling of the microscale cell was performed,and its elastic performance parameters were predicted using two homogenization methods,examining the impact of fluctuations in microscale cell parameters on composite material performance.A finite element model of the CFRP drive shaft was then constructed,achieving parameter transfer between microscale and macroscale through Python programming.This enabled an investigation into the influence of both micro and macro design parameters on the CFRP drive shaft’s performance.The Multi-Objective Particle Swarm Optimization(MOPSO)algorithm was enhanced for particle generation and updating strategies,facilitating the resolution of multi-objective reliability optimization problems,including composite material layup process constraints.Case studies demonstrated that this approach leads to over 30%weight reduction in CFRP drive shafts compared to metallic counterparts while satisfying reliability requirements and offering insights for the lightweight design of other vehicle components.

Development and Comparison of Hybrid Genetic Algorithms for Network Design Problem in Closed Loop Supply Chain

This paper presents four different hybrid genetic algorithms for network design problem in closed loop supply chain. They are compared using a complete factorial experiment with two factors, viz. problem size and algorithm. Based on the significance of the factor “algorithm”, the best algorithm is identified using Duncan’s multiple range test. Then it is compared with a mathematical model in terms of total cost. It is found that the best hybrid genetic algorithm identified gives results on par with the mathematical model in statistical terms. So, the best algorithm out of four algorithm proposed in this paper is proved to be superior to all other algorithms for all sizes of problems and its performance is equal to that of the mathematical model for small size and medium size problems.

Robust Multiobjective and Multidisciplinary Design Optimization of Electrical Drive Systems

Design and optimization of electrical drive systems often involve simultaneous consideration of multiple objectives that usually contradict to each other and multiple disciplines that normally coupled to each other.This paper aims to present efficient system-level multiobjective optimization methods for the multidisciplinary design optimization of electrical drive systems.From the perspective of quality control,deterministic and robust approaches will be investigated for the development of the optimization models for the proposed methods.Meanwhile,two approximation methods,Kriging model and Taylor expansion are employed to decrease the computation/simulation cost.To illustrate the advantages of the proposed methods,a drive system with a permanent magnet synchronous motor driven by a field oriented control system is investigated.Deterministic and robust Pareto optimal solutions are presented and compared in terms of several steady-state and dynamic performances(like average torque and speed overshoot)of the drive system.The robust multiobjective optimization method can produce optimal Pareto solutions with high manufacturing quality for the drive system.

Optimum Determination of Partial Transmission Ratios of Mechanical Driven Systems Using a Chain Drive and a Two-step Helical Gearbox

This paper presents a study on optimum determination of partial ratios of mechanical drive systems using a chain drive and two-step helical gearbox for getting minimum size of the system. The chosen objective function was the cross section dimension of the system. In solving the optimization problem, the design equation for pitting resistance of a gear set was investigated and equations on moment equilibrium condition of a mechanic system including a chain drive and two helical gear units and their regular resistance condition were analyses. From the results of the study, effective formulas for determination of the partial ratios of the chain drive and two-step helical gearboxes were introduced. As the formulas are explicit, the partial ratios can be calculated accurately and simply.

Optimum Structural Design of a Chain-Driving Pumping Unit

In this paper the pumping unit of type QLCJ14-6 is studied.Through the belt driving unit,the mo-tor drives the driving sprocket in which the rotation rate has been reduced by the reduction ge arbox.The locus chain moves between the driving sprocket and upper sprocket which are vertically set.There's a special chain element in the locus chain,which drives the reciprocating holster with the main shaft linchpin and slide block.The r reciprocating g holster could only move up and down when the locus chain moves in a circle.In this way the up and down stroke of the sucker rod and the mac hine is realized.The lower end of the reciprocating holster is con-nected with the equilibrium system to make the structure balance.The balancing cylinder is re-placed by the balancing block to make the structure simplified.

Remanufacturing closed-loop supply chain network design based on genetic particle swarm optimization algorithm

As the huge computation and easily trapped local optimum in remanufacturing closed-loop supply chain network (RCSCN) design considered, a genetic particle swarm optimization algorithm was proposed. The total cost of closed-loop supply chain was selected as fitness function, and a unique and tidy coding mode was adopted in the proposed algorithm. Then, some mutation and crossover operators were introduced to achieve discrete optimization of RCSCN structure. The simulation results show that the proposed algorithm can gain global optimal solution with good convergent performance and rapidity. The computing speed is only 22.16 s, which is shorter than those of the other optimization algorithms.

Optimization and Performance Comparison of Hairpin?Winding PMSM for Electric Vehicles Under Drive Cycle

Aiming at the problem of large AC copper loss caused by skin effects and proximity effects,and low efficiency at high speed of the hairpin-winding permanent magnet synchronous motor(PMSM)for electric vehicles(EVs),this paper firstly established the electromagnetic analytical model of the hairpin winding to calculate AC resistance.And the finite element model(FEM)of the hairpin-winding driving motor is established to calculate the AC characteristic of the hairpin winding at different speeds and temperatures.Then,combining modified particle swarm optimization(MPSO)and FEM,a 60 k W hairpin-winding PMSM is optimized under driving cycle conditions,and the electromagnetic performance and heat dissipation performance are compared with that of the traditional strand-winding motor.Finally,a prototype is made and an experimental platform is built to test the efficiency Map and temperature rise of the hairpin-winding motor over the whole speed range and verify the accuracy of the proposed optimization design method.The results show that the hairpin-winding PMSM not only has higher slot filling rate,high?efficiency range and power density,but also has better heat dissipation performance,which is suitable for application in the field of electric vehicles.

Optimization and implementation strategy of ESCO driving force in the development of energy-saving transformation market of existing buildings

The development of the existing building energy-saving transformation market is inseparable from the internal driving force of ESCO.Giving full play to the driving role of ESCO scientifically is the internal requirement to promote the healthy and orderly operation of the existing building energy-saving transformation market.This paper summarizes the practical experience of developing ESCO driving force operation in foreign existing building energy-saving transformation market,analyzes the bottleneck of developing ESCO driving force operation in China’s existing building energy-saving transformation market,and puts forward useful practical enlightenment based on the comparison between home and abroad;According to the optimization principle of ESCO driving force operation in the development of existing building energy-saving transformation market,the optimization design framework of ESCO driving force is proposed,and the implementation strategy of ESCO driving force optimization in the development of existing building energy-saving transformation market is planned.In order to optimize and improve the effectiveness of the operation and development of the energy-saving transformation market of existing buildings with the internal driving force of ESCO.

Optimization of PCR Reaction System for Random Single-strand DNA Pool in SELEX Technology

[Objective] This study aimed to optimize the PCR amplification conditions for random ssDNA pool in SELEX technology. [Method] L16（45） orthogonal experimental design was adopted for optimization of five important factors affecting PCR reaction system for random single-stranded DNA pool including Mg2＋ concentration, dNTP concentration, amount of Taq DNA polymerase, primer concentration and amount of random single-stranded DNA pool at four levels. Meanwhile, the annealing temperature and number of PCR reaction cycles were optimized to establish the optimal reaction system and PCR procedure. [Result] The optimal combination of PCR reaction system for random ssDNA pool was obtained, with a total system volume of 20 μl containing 2.0 μl of 10 × Buffer, 0.5 ng of random ssDNA pool, 2.5 mmol/L Mg2＋, 0.25 mmol/L dNTP Mixture, 0.6 μmol/L upstream and downstream primers and 1.5 U of Taq DNA polymerase; the optimal annealing temperature was 68 ℃ and the optimal number of cycles was 12. Under the above conditions, clear and stable bands with high specificity for random ssDNA pool were amplified. [Conclusion] This study laid the foundation for selection of parameters with higher specificity in SELEX technology.

Method of Electric Powertrain Matching for Battery-powered Electric Cars

The current match method of electric powertrain still makes use of longitudinal dynamics, which can’t realize maximum capacity for on-board energy storage unit and can’t reach lowest equivalent fuel consumption as well. Another match method focuses on improving available space considering reasonable layout of vehicle to enlarge rated energy capacity for on-board energy storage unit, which can keep the longitudinal dynamics performance almost unchanged but can’t reach lowest fuel consumption. Considering the characteristics of driving motor, method of electric powertrain matching utilizing conventional longitudinal dynamics for driving system and cut-and-try method for energy storage system is proposed for passenger cars converted from traditional ones. Through combining the utilization of vehicle space which contributes to the on-board energy amount, vehicle longitudinal performance requirements, vehicle equivalent fuel consumption level, passive safety requirements and maximum driving range requirement together, a comprehensive optimal match method of electric powertrain for battery-powered electric vehicle is raised. In simulation, the vehicle model and match method is built in Matlab/simulink, and the Environmental Protection Agency (EPA) Urban Dynamometer Driving Schedule (UDDS) is chosen as a test condition. The simulation results show that 2.62% of regenerative energy and 2% of energy storage efficiency are increased relative to the traditional method. The research conclusions provide theoretical and practical solutions for electric powertrain matching for modern battery-powered electric vehicles especially for those converted from traditional ones, and further enhance dynamics of electric vehicles.

Effects of structural parameters and rigidity of driving diaphragm on flow characteristics of micro valveless pump

The structure and operating principle of micro valveless pump were investigated theoretically and experimentally. The mathematical model of pressure and flow rate within the micro nozzle/diffuser was established to analyze the effects of nozzle/diffuser parameters on the output flow rate of the micro valveless pump.The experiments were carried out with different structural parameters, driving frequencies, vibration amplitudes and stiffness of the driving diaphragms. Effects of the structural parameters and driving conditions on the operation performance of the pump are discussed in detail. The work provides useful reference for structure optimization selection of the driving diaphragm of micro valveless pump.

数字化背景下制鞋行业供应链优化研究

供应链优化对制鞋行业具有重要影响。数字化技术能够帮助企业实现自动化和智能化生产,同时也为企业的供应链优化提供了方向。本文在分析数字化与供应链关系的基础上,结合我国制鞋行业的发展现状,阐述现阶段制鞋行业供应链管理存在的问题,并探讨供应链优化的意义。最后,针对性地提出制鞋企业如何结合数字化发展进行供应链优化的建议,为我国制鞋企业的供应链建设提供借鉴。

微小流量旋转直驱伺服阀传控特性分析与优化

针对无人机、战术弹、支线民航等小型飞行器航空发动机燃油计量系统与推力矢量系统微小流量的伺服控制需求,就旋转直驱伺服阀偏心球副传动接口与非全周节流阀口等关键结构进行了尺寸约束设计分析,并就节流阀口宽度、球副偏心距以及驱动电机转动惯量等重要参数进行了优化分析,给出了伺服阀结构设计的优化区间。在此基础上,研究提出了电机转角与电流双闭环控制方法,幅频响应实测结果与理论分析较为一致,200 Hz以上高频响应满足实际需求,且双闭环控制方法大幅降低了伺服阀响应超调并提升了稳定性。

港口重载AGV驱动防滑设计

针对港口重载自动导引运输车(AGV)工作中遇到的过度滑转危险,文中提出一种基于最佳滑转率控制的驱动防滑设计。该设计根据港口环境特点建立路面附着特性模型;选用T-S型模糊控制器进行港口路面模糊识别设计,对峰值纵向附着系数及最佳滑转率进行识别,并将识别结果用于最佳滑转率控制中,进而提升港口AGV驱动防滑性能。通过单一路面与对接路面识别试验,验证了港口路面模糊识别器具有准确识别能力。

促进幼儿深度学习的项目式活动中驱动性问题链的设计

驱动性问题是项目式学习的核心与灵魂,是项目式活动的抓手,能够促进幼儿的深度学习,是培养幼儿核心素养的重要途径。探讨驱动性问题的内涵及设计,从教与学角度及项目学习的基本要素角度着手,分析驱动性问题在项目式活动中的引领作用,形成驱动性问题解决模式,用驱动性问题链引领项目活动的开展,促进幼儿的学习及深层次发展。

铁路工程建设可持续供应链网络集成优化研究

随着国家对铁路工程项目可持续发展的日益重视,迫切需要先进且集成的供应链网络设计方案理论与方法来提高供应链效率、可持续绩效以及资源利用率。实施可持续供应链网络设计已成为实现铁路工程可持续发展的重要途径,而供应商选择、物流设施选址、路径规划、库存管理以及工程废弃物回收再利用等决策是铁路工程供应链管理的核心与关键问题。针对我国铁路工程建设供应链管理特点,从可持续视角研究铁路工程建设供应链网络设计集成优化问题,提出两阶段的求解框架:其中,第1阶段基于可持续指标体系运用模糊TOPSIS方法确定最佳供应商选择;第2阶段针对物流设施选址、库存控制策略与网络最佳流量分配的集成决策问题,构建了基于模糊规划的多周期多目标供应链网络集成决策优化模型。该优化模型考虑了运输过程的不确定性,以供应链总成本、碳排放量最小以及社会效益最大为优化目标。针对上述多周期多目标优化模型的特征,设计了改进的宽容分层序列算法进行求解。最后,基于我国丰雄商铁路工程建设项目进行案例研究,验证了上述求解框架与算法的有效性,并针对单位运价、单位运输碳排放量以及弃置率3个关键参数进行了敏感性分析。研究结果表明:1)批量折扣策略可以在联合采购中节省大量成本;2)运输模式与路径优化对系统的效率和可持续绩效有决定性影响;3)与管理学手段相比,推进新能源的使用是降低碳排放量最有效的措施;4)社会效益的提高不可避免地需要更高的成本,政府合理的补贴政策是提高企业积极性的关键举措;5)长远来看,铁路工程项目中的废弃物回收利用是实现可持续工程建设的重要途径,其技术和应用的发展都应受到重视。

一种蜗杆传动多目标优化设计方法

蜗杆传动的传统设计方法主要是设计者借鉴已有的设计实例和经验,首先试选基本参数,再通过校核确定该参数是否满足使用要求。若不满足要求,则重新选择参数进行校核,若满足要求则作为最终的设计方案。由于不同设计者选择的参数一般不同,就会导致同一设计要求出现不同设计方案的现象,且方案一般不是最佳。多目标优化设计方法在排除传统设计方法人为主观因素的基础上,以与蜗杆制造成本和传动性能紧密相关的蜗轮齿冠体积、蜗杆传动中心距、滑动速度等目标为优化对象,建立优化目标函数,确定设计约束条件,利用有关软件优化工具箱寻找最优解进行优化。结果表明,多目标优化设计与常规设计相比,在传动效率小幅提升的前提下,多目标优化设计的蜗轮齿冠体积大幅下降65.42%,传动中心距缩小24.8%,优化设计效果显著,优化后机构综合性能更强。

考虑节点中断风险的弹性供应链设计方法

供应链全球化发展为企业带来广阔前景,但庞大的供应链体系也造成供应链中断风险激增,为企业带来了巨大潜在风险。然而,由于供应链中断风险难以预知,针对中断的弹性供应链优化设计方法还远不成熟。在此背景下,建立了一种新颖的弹性供应链设计优化方法,旨在增强供应链抵御中断的能力。提出并定义了节点中断风险评价指标(NDII),以反映节点中断对供应链的影响程度。定义风险系数(RW)以表征供应链风险程度,避免了对风险场景及其概率分布的预测,同时体现企业对供应链弹性的重视程度。基于鲁棒优化(RO)方法,建立了对高风险节点惩罚的NDII-RO优化方法,并应用于广东省生物燃料供应链优化设计。优化结果表明该方法可实现抵御中断风险的弹性供应链设计。

基于定子全浸式及绕组内冷式的蒸发冷却永磁直驱风力发电机优化设计研究

为了充分发挥蒸发冷却技术在风力发电领域中高效的散热性能以及免维护的自循环特性,本文基于发电机定子全浸泡以及绕组空心导线内冷的两种散热形式,对一系列不同功率等级下的直驱式永磁风力发电机进行了优化设计研究,并对不同冷却技术路线下的电机优化设计方案进行了对比和分析。本文首先分析了不同技术路线下不同蒸发冷却系统各自所具有的特点及优势;之后基于电磁场和传热学理论建立了发电机电磁参数及温度场的分析计算模型,并基于冷却系统的结构布局分析了不同技术路线下发电机定子的传热特性;最后基于发电机电磁场和温度场的耦合分析建立了风力发电机的优化设计模型,通过多目标遗传优化算法,对2MW、5MW和10MW三种不同功率等级下的直驱式永磁风力发电机进行了以材料和成本为目标的电机系统优化设计。优化结果及对比分析表明,针对兆瓦级直驱式风力发电机而言,采用空心导线内冷式技术更具有设计成本和冷却性能上的优势,本文中的优化方法和策略可以为蒸发冷却永磁直驱式风力发电机的优化设计提供理论依据和设计基础。