采用NSGA-Ⅱ算法的车载复合电源参数匹配

提出了一种主动并联式车载复合电源的参数匹配/能量管理联合优化方法。首先,根据整车性能指标确定电池组和超级电容组的容量范围,并针对部件性能制定能量管理策略,然后,以复合电源替换成本和日均电耗最小为目标建立多目标优化函数,采用受控精英多目标遗传算法(Controlled elitist NSGA-Ⅱ)在不同的日均里程下对复合电源参数和能量管理策略同时进行优化,得到对应的Pareto解集,作为备选。综合考虑备选集的初始成本、百公里总成本和电池组寿命里程,优选电池组和超级电容组参数。优化结果表明:日均里程在48km以内时,匹配22kW·h电池组,超过48km后,里程越大,匹配电池组容量越大;在不同的日均里程下,不同容量的电池组匹配一个60 W·h左右的超级电容组可以达到综合性能最优。与电池单独优化相比,电源替换成本平均降低11.5%,寿命里程平均提高19.8%,日均总成本平均降低13.2%。

重载物流AGV机器人悬架结构优化设计

为提高重载物流AGV机器人的路面适应能力,设计适合物流仓储车间的AGV移动系统。为该系统构建纵臂式独立悬架,具有调节机构以改变减振器角度和纵臂长度。基于简化的悬架系统支架模型,进行静力学特性分析;构建以支架不同尺寸参数为变量,以结构质量为目标函数,以最大变形量和最大等效应力为约束条件的优化数学模型,采用受控精英多目标遗传算法对设计变量进行优化。校核优化后结构强度和刚度满足使用要求,证明了结构优化的合理性,实现了构件精益制造,提高了材料的利用率。

Multi-objective optimization design for leg mechanism of hydraulic-actuated quadruped robot

In order to improve the robot＇ s abilities of bearing heavy burdens and transporting in complex terrains, the multi-objective optimization design for leg mechanism of the quadruped robot with hydraulic actuated is studied in this paper. The kinematics and dynamics of the robot are ana- lyzed and the two-dimensional linear inverted pendulum model is adopted in planning the trajectories of joints. Then the mathematical model of valve-controlled asymmetric cylinder and control model of single leg are proposed respectively. In the end, NSGA-Ⅱ algorithm is used to achieve the multi^ob- jective optimization design of parameters concerning single leg mechanism and PD torque control. The results prove that the optimized leg mechanism can significantly reduce the required maximum power of hydraulic system, thus decrease its own weight and lead to the obtaining of good dynamic performance.

Small-signal Analysis of DC Microgrid and Multi-objective Optimization Segmented Droop Control Suitable for Economic Dispatch

To obtain a larger controllable range of output/input power of droop-control sources,a multi-objective optimization segmented droop control suitable for economic dispatch for a DC microgrid is proposed.According to the small-signal analysis,the worst point of the stability in the droop-control curve is determined through the analysis of a simplified model with multiple droop-control sources.By considering the worst points of stability as constraints,an elitist non-dominated sorting genetic algorithm is used to search the better turning points of the proposed droop-control curves after obtaining the new rated operation points from the system-layer economic dispatch.Simultaneously,optimization objectives,including the influence of eliminating the line resistance and capacity matching,are considered in the search process.Finally,the simulation results of the DC microgrid simulation model based on RT-Lab are presented to support the stability conclusion and proposed droop control.

变切深工况下恒定切削力约束的多目标进给量优化方法

针对数控加工中工艺人员设定恒定的进给量导致零件加工效率低、表面质量差的问题,提出基于恒定切削力约束的多目标进给量优化方法。以切削力预测模型为基础,以综合考虑提高零件加工效率和表面质量为优化目标,以恒定切削力,机床参数,加工表面质量和进给量平滑过渡为约束条件,建立了多目标进给量优化模型。通过正交切削试验标定切削力系数,并验证了预测模型的正确性和精确性。通过试切工件采集原始切削力,并试验分析确定出最优目标切削力值,采用基于精英控制的非支配筛选遗传算法(Controlled elitist non-dominated sorting genetic algorithm,Controlled NSGA-Ⅱ)对进给量进行了优化。试验结果验证了恒定切削力约束的多目标进给量优化模型的有效性,达到了恒定切削力约束目标,保证了加工表面质量,提高了加工效率,实现了数控加工工艺参数优化,提高了数控系统应用性能。