摘要
在轨道交通向低碳化、智能化方向发展的需求驱动下,用于实现轨道车辆在线状态智能监测的小型车载传感设备的无源无线化日趋广泛。压电响应元件可以将轨道车辆振动能量用于供电,从而避免采用传统的电池和外部接线方式,减少车辆改造及维护成本、增强系统的抗干扰能力。但是由于压电元件在工程应用中普遍存在着工作频率与振源频率匹配偏差问题,其俘获振动能量的能力难以得到有效的开发。针对这一问题,提出一种对扇形压电悬臂梁元件进行频率匹配最优化设计的方法:为了大幅减少有限元仿真精确计算的次数、节约设计时间,使用拉丁超立方采样法从参数化的ANSYS有限元模型中获取用于训练模型的样本点集,建立精确度较高的Kriging代理模型;通过实际测试采集、分析轴箱处固有的频域振动特性;以压电梁的工作频率点与轴箱振动频率集中点的距离、结构自重最小构建多目标优化模型,采用基于分解和检测-逃逸策略的多目标进化优化算法(MOEA/D-DAE)求解,获得相对较优的解的集合——Pareto前沿;最后采用聚合树方法筛选出最优解。研究结果表明:所采用的方法相比于NSGA-II降低了计算复杂度、设计准确性高,输出电压最高提升至初始设计的219%,理论最大输出功率相比于初始设计提高了0.28 W,得出的最优化设计在输出电压和理论输出功率方面得到了显著提升,为实现车载自供电设备的最优化设计提供了理论参考。
Driven by the requirements for low-carbon and intellectual development of rail transit,the passive wireless of small-scale onboard sensing devices for the intelligent monitoring of the online state of rail vehicles has become increasingly widespread.Piezoelectric response elements can use the vibration energy of rail vehicles for power supply,thereby avoiding the use of traditional batteries and external wiring methods,reducing vehicle transformation and maintenance costs,and enhancing the anti-interference ability of the system.However,because piezoelectric components generally have the problem of matching deviation between the working frequency and the frequency of the vibration source in engineering applications,its ability to capture vibration energy is difficult to be effectively developed.In response to this problem,this paper proposed a method to optimize the frequency matching design of the sector-shaped piezoelectric cantilever beam element.In order to greatly reduce the number of precise calculations for finite element simulation and save design time,the Latin Hypercube Sampling method was used to obtain the sample point set for training the model from the parameterized ANSYS finite element model.And a more accurate Kriging surrogate model was established.Through actual testing,the inherent frequency domain vibration characteristics of the axle box were collected and analyzed.The multi-objective optimization model was constructed based on the distance between the working frequency point of the piezoelectric beam and the vibration frequency concentration point of the axle box,and the minimum structural weight.The multi-objective evolutionary optimization algorithm(MOEA/D-DAE)based on decomposition and detection-escape strategy was used to solve the problem.And a relatively optimal set of solutions-Pareto frontier was obtained.Finally,the aggregation tree method was used to screen out the optimal solution.The research results show that the method used in this paper reduces the computational complexity and design accuracy compared with the traditional method.The output voltage is increased to 219%of the initial design,and the theoretical maximum output power is increased by 0.28 W compared with the initial design.The optimized design obtained has been significantly improved in output voltage and theoretical output power,which provides a theoretical reference for realizing the optimal design of onboard self-powered equipment.
作者
孙佳慧
钟倩文
郑树彬
彭乐乐
文静
SUN Jiahui;ZHONG Qianwen;ZHENG Shubin;PENG Lele;WEN Jing(School of Urban Rail Transit,Shanghai University of Engineering Science,Shanghai 201620,China)
出处
《铁道科学与工程学报》
EI
CAS
CSCD
北大核心
2022年第9期2709-2719,共11页
Journal of Railway Science and Engineering
基金
国家自然科学基金资助项目(51975347,51907117)。
关键词
轨道车辆
振动能量收集
压电俘能器
代理模型
优化算法
rail vehicle
vibration energy harvesting
piezoelectric energy harvester
surrogate model
optimization algorithm
