Statistical Energy Analysis(SEA) is one of the conventional tools for predicting vehicle high-frequency acoustic responses.This study proposes a new method that can provide customized optimization solutions to meet NV...Statistical Energy Analysis(SEA) is one of the conventional tools for predicting vehicle high-frequency acoustic responses.This study proposes a new method that can provide customized optimization solutions to meet NVH targets based on the specific needs of different project teams during the initial project stages.This approach innovatively integrates dynamic optimization,Radial Basis Function(RBF),and Fuzzy Design Variables Genetic Algorithm(FDVGA) into the optimization process of Statistical Energy Analysis(SEA),and also takes vehicle sheet metal into account in the optimization of sound packages.In the implementation process,a correlation model is established through Python scripts to link material density with acoustic parameters,weight,and cost.By combining Optimus and VaOne software,an optimization design workflow is constructed and the optimization design process is successfully executed.Under various constraints related to acoustic performance,weight and cost,a globally optimal design is achieved.This technology has been effectively applied in the field of Battery Electric Vehicle(BEV).展开更多
Statistical energy analysis (SEA) is an effective method for predicting high frequency vibro-acoustic performance of automobiles. A full vehicle SEA model is presented for interior noise reduction. It is composed of a...Statistical energy analysis (SEA) is an effective method for predicting high frequency vibro-acoustic performance of automobiles. A full vehicle SEA model is presented for interior noise reduction. It is composed of a number of subsystems based on a 3D model with all parameters for each subsystem. The excitation inputs are measured through road tests in different conditions,including inputs from the engine vibration and the sound pressure of the engine bay. The accuracy in high frequency of SEA model is validated,by comparing the analysis results with the testing pressure level data at driver's right ear. Noise contribution and sensitivity of key subsystems are analyzed. Finally,the effectiveness of noise reduction is verified. Based on the SEA model,an approach combining test and simulation is proposed for the noise vibration and harshness (NVH) design in vehicle development. It contains building the SEA model,testing for subsystem parameter identification,validating the simulation model,identifying subsystem power inputs,analyzing the design sensitivity. An example is given to demonstrate the interior noise reduction in high frequency.展开更多
In this paper, a technical and statistical analysis of security system and security management is provided for crowd energy and smart living. At the same time, a clear understanding is made for crowd energy concept an...In this paper, a technical and statistical analysis of security system and security management is provided for crowd energy and smart living. At the same time, a clear understanding is made for crowd energy concept and next generation smart living. Various case examples have been studied and a brief summary has been provided.Furthermore, a statistical analysis has been provided in terms of security management in smart living where it is found that young technocrats give the highest importance to security management in smart living. Last but not the least, current limitation, constraints, and future scope of security implementation have been discussed in terms of crowd energy clustered with next generation smart living.展开更多
Crashworthiness and lightweight optimization design of the crash box are studied in this paper. For the initial model, a physical test was performed to verify the model. Then, a parametric model using mesh morphing te...Crashworthiness and lightweight optimization design of the crash box are studied in this paper. For the initial model, a physical test was performed to verify the model. Then, a parametric model using mesh morphing technology is used to optimize and decrease the maximum collision force (MCF) and increase specific energy absorption (SEA) while ensure mass is not increased. Because MCF and SEA are two conflicting objectives, grey relational analysis (GRA) and principal component analysis (PCA) are employed for design optimization of the crash box. Furthermore, multi-objective analysis can convert to a single objective using the grey relational grade (GRG) simultaneously, hence, the proposed method can obtain the optimal combination of design parameters for the crash box. It can be concluded that the proposed method decreases the MCF and weight to 16.7% and 29.4% respectively, while increasing SEA to 16.4%. Meanwhile, the proposed method in comparison to the conventional NSGA-Ⅱ method, reduces the time cost by 103%. Hence, the proposed method can be properly applied to the optimization of the crash box.展开更多
为了对空间光学遥感器进行冲击响应预测,提出了一种基于统计能量分析(Statistical Energy Analysis,SEA)原理的新方法;基于稳态SEA推导了瞬态SEA的能量流平衡方程,结合虚拟模态综合与仿真方法(Virtual Mode Synthesis and Simulation,VM...为了对空间光学遥感器进行冲击响应预测,提出了一种基于统计能量分析(Statistical Energy Analysis,SEA)原理的新方法;基于稳态SEA推导了瞬态SEA的能量流平衡方程,结合虚拟模态综合与仿真方法(Virtual Mode Synthesis and Simulation,VMSS)和SEA方法进行空间光学遥感器的冲击响应预测;首先根据SEA原理,建立了典型空间光学遥感器的简化SEA模型,采用理论计算和试验测试的方法,得到了该模型各子系统的模态密度、内损耗因子、耦合损耗因子;在火工品附近安装冲击加速度传感器,点火起爆,测得冲击加速度时域曲线,以该测试数据为分析模型的输入,基于SEA方法进行冲击响应分析,得到反射镜子系统、遮光罩子系统、载荷板子系统的冲击响应谱曲线,该曲线与试验数据比对表明,在低频段由于模态密度较低,预测精度较差,在高频段其一致性小于4d B,从而验证了该方法在结构高频冲击响应预测的有效性。展开更多
关于整车车内噪声的仿真分析方法,在理论上,FEM/BEM方法可以进行全频段的仿真,但由于高频噪声的波长短,且在仿真初期结构材料的参数不确定,FEM/BEM参数识别和计算难度大,在这种情况下,基于能量平均思想的统计能量方法显现出其特定的求...关于整车车内噪声的仿真分析方法,在理论上,FEM/BEM方法可以进行全频段的仿真,但由于高频噪声的波长短,且在仿真初期结构材料的参数不确定,FEM/BEM参数识别和计算难度大,在这种情况下,基于能量平均思想的统计能量方法显现出其特定的求解优势。针对SEA分析方法理论就该方法在车内噪声应用领域展开探讨,从整车车内噪声激励源及噪声传递途径、整车NVH性能开发方法和整车SEA建模方法三个角度对车内高频噪声仿真进行阐述。SEA仿真在整车方面的应用现阶段主要用来指导声学包开发,对SEA仿真中的关键科学问题与工程实际的结合,介绍2个典型工程案例:其一基于双墙理论的车门隔声量优化,通过建立相对独立的双墙模型,提高建模过程中的仿真精度;其二通过控制声学包装优化变速箱高频啸叫,采用车内双层地毯的优化方法,降低驾驶员头部的声压1.31 d B。通过SEA方法对车内高频噪声进行仿真显著改善车辆的NVH性能,提高车辆乘坐舒适性,可为相关领域的研究提供参考及借鉴。展开更多
文摘Statistical Energy Analysis(SEA) is one of the conventional tools for predicting vehicle high-frequency acoustic responses.This study proposes a new method that can provide customized optimization solutions to meet NVH targets based on the specific needs of different project teams during the initial project stages.This approach innovatively integrates dynamic optimization,Radial Basis Function(RBF),and Fuzzy Design Variables Genetic Algorithm(FDVGA) into the optimization process of Statistical Energy Analysis(SEA),and also takes vehicle sheet metal into account in the optimization of sound packages.In the implementation process,a correlation model is established through Python scripts to link material density with acoustic parameters,weight,and cost.By combining Optimus and VaOne software,an optimization design workflow is constructed and the optimization design process is successfully executed.Under various constraints related to acoustic performance,weight and cost,a globally optimal design is achieved.This technology has been effectively applied in the field of Battery Electric Vehicle(BEV).
基金Sponsored by the Key Project of the Development of Science and Technology of Jilin Province (20040332-1)the National"863"Project(2006AA110102-3)
文摘Statistical energy analysis (SEA) is an effective method for predicting high frequency vibro-acoustic performance of automobiles. A full vehicle SEA model is presented for interior noise reduction. It is composed of a number of subsystems based on a 3D model with all parameters for each subsystem. The excitation inputs are measured through road tests in different conditions,including inputs from the engine vibration and the sound pressure of the engine bay. The accuracy in high frequency of SEA model is validated,by comparing the analysis results with the testing pressure level data at driver's right ear. Noise contribution and sensitivity of key subsystems are analyzed. Finally,the effectiveness of noise reduction is verified. Based on the SEA model,an approach combining test and simulation is proposed for the noise vibration and harshness (NVH) design in vehicle development. It contains building the SEA model,testing for subsystem parameter identification,validating the simulation model,identifying subsystem power inputs,analyzing the design sensitivity. An example is given to demonstrate the interior noise reduction in high frequency.
基金the support provided by the University of Asia Pacific and Institute for Energy, Environment, Research and Development (IEERD)
文摘In this paper, a technical and statistical analysis of security system and security management is provided for crowd energy and smart living. At the same time, a clear understanding is made for crowd energy concept and next generation smart living. Various case examples have been studied and a brief summary has been provided.Furthermore, a statistical analysis has been provided in terms of security management in smart living where it is found that young technocrats give the highest importance to security management in smart living. Last but not the least, current limitation, constraints, and future scope of security implementation have been discussed in terms of crowd energy clustered with next generation smart living.
基金Supported by the National Key Research and Development Project(2016YFB0101601)
文摘Crashworthiness and lightweight optimization design of the crash box are studied in this paper. For the initial model, a physical test was performed to verify the model. Then, a parametric model using mesh morphing technology is used to optimize and decrease the maximum collision force (MCF) and increase specific energy absorption (SEA) while ensure mass is not increased. Because MCF and SEA are two conflicting objectives, grey relational analysis (GRA) and principal component analysis (PCA) are employed for design optimization of the crash box. Furthermore, multi-objective analysis can convert to a single objective using the grey relational grade (GRG) simultaneously, hence, the proposed method can obtain the optimal combination of design parameters for the crash box. It can be concluded that the proposed method decreases the MCF and weight to 16.7% and 29.4% respectively, while increasing SEA to 16.4%. Meanwhile, the proposed method in comparison to the conventional NSGA-Ⅱ method, reduces the time cost by 103%. Hence, the proposed method can be properly applied to the optimization of the crash box.
文摘为了对空间光学遥感器进行冲击响应预测,提出了一种基于统计能量分析(Statistical Energy Analysis,SEA)原理的新方法;基于稳态SEA推导了瞬态SEA的能量流平衡方程,结合虚拟模态综合与仿真方法(Virtual Mode Synthesis and Simulation,VMSS)和SEA方法进行空间光学遥感器的冲击响应预测;首先根据SEA原理,建立了典型空间光学遥感器的简化SEA模型,采用理论计算和试验测试的方法,得到了该模型各子系统的模态密度、内损耗因子、耦合损耗因子;在火工品附近安装冲击加速度传感器,点火起爆,测得冲击加速度时域曲线,以该测试数据为分析模型的输入,基于SEA方法进行冲击响应分析,得到反射镜子系统、遮光罩子系统、载荷板子系统的冲击响应谱曲线,该曲线与试验数据比对表明,在低频段由于模态密度较低,预测精度较差,在高频段其一致性小于4d B,从而验证了该方法在结构高频冲击响应预测的有效性。
文摘关于整车车内噪声的仿真分析方法,在理论上,FEM/BEM方法可以进行全频段的仿真,但由于高频噪声的波长短,且在仿真初期结构材料的参数不确定,FEM/BEM参数识别和计算难度大,在这种情况下,基于能量平均思想的统计能量方法显现出其特定的求解优势。针对SEA分析方法理论就该方法在车内噪声应用领域展开探讨,从整车车内噪声激励源及噪声传递途径、整车NVH性能开发方法和整车SEA建模方法三个角度对车内高频噪声仿真进行阐述。SEA仿真在整车方面的应用现阶段主要用来指导声学包开发,对SEA仿真中的关键科学问题与工程实际的结合,介绍2个典型工程案例:其一基于双墙理论的车门隔声量优化,通过建立相对独立的双墙模型,提高建模过程中的仿真精度;其二通过控制声学包装优化变速箱高频啸叫,采用车内双层地毯的优化方法,降低驾驶员头部的声压1.31 d B。通过SEA方法对车内高频噪声进行仿真显著改善车辆的NVH性能,提高车辆乘坐舒适性,可为相关领域的研究提供参考及借鉴。
