scholarly journals A Load Fluctuation Characteristic Index and Its Application to Pilot Node Selection

Energies ◽  
2014 ◽  
Vol 7 (1) ◽  
pp. 115-129 ◽  
Author(s):  
Huaichang Ge ◽  
Qinglai Guo ◽  
Hongbin Sun ◽  
Bin Wang ◽  
Boming Zhang ◽  
...  
Keyword(s):  
Node Selection ◽  
Characteristic Index ◽  
Fluctuation Characteristic ◽  
Load Fluctuation

An Evaluation of Control Parameters for Load Fluctuation Compensation by Battery Control Aimed at Reducing Peak Demand for a Building

2015 ◽  
Vol 135 (1) ◽  
pp. 71-77
Author(s):  
Takayuki Sugimoto ◽  
Eisuke Shimoda ◽  
Toshihiro Yamane ◽  
Shigeo Numata
Keyword(s):  
Control Parameters ◽  
Peak Demand ◽  
Load Fluctuation

scholarly journals Analysis and optimization of the vehicle handling stability with considering suspension kinematics and compliance characteristics

2021 ◽  
Vol 13 (5) ◽  
pp. 168781402110155
Author(s):  
Jin Gao ◽  
Fuquan Wu
Keyword(s):  
Dynamic Model ◽  
Great Influence ◽  
Transient State ◽  
Transient Characteristic ◽  
Nsga Ii ◽  
Pareto Solution ◽  
Characteristic Index ◽  
Yaw Rate ◽  
Comparison Results ◽  
Force Calculation

The dynamic model of the front double wishbone suspension and the rear multi-link suspension of the vehicle are established. On the basis of detailed analysis of suspension kinematics, calculation method of wheel alignment angle and force calculation of suspension bushing, the influence mechanism of suspension bushing on the vehicle transient state is clarified, and the vehicle transient characteristic index is derived from the vehicle three-free dynamic model. The sensitivity analysis of the suspension bushing is carried out, and the bushing stiffness which has a great influence on the transient state of the vehicle is obtained. The bushing stiffness scale factor is used as the optimization variable, the vehicle transient characteristic index is used as the optimization target, and the NSGA-II optimization algorithm is used for multi-objective optimization. After optimization, one Pareto solution is selected to compare with the original vehicle, the comparison results show that the yaw rate gain, resonance frequency and delay time of yaw rate in the vehicle transient characteristic index are all improved, other optimization targets change less. In the steady-state comparison, the understeer tendency of the vehicle increases, and the roll angle of the vehicle increases but is within an acceptable range.

Multiple performance characteristic index optimization of dimensional accuracy and geometrical shape angle in turn-mill multitasking machining

2021 ◽  
pp. 095440542110285
Author(s):  
Wei-Tai Huang ◽  
Shih-Cheng Yang ◽  
Wen-Hsien Ho ◽  
Jinn-Tsong Tsai
Keyword(s):  
Performance Characteristic ◽  
Fuzzy Theory ◽  
Dimensional Accuracy ◽  
Processing Parameters ◽  
Geometrical Shape ◽  
Characteristic Index ◽  
Control Factors ◽  
Experimental Sequence ◽  
Gray Correlation ◽  
Robust Process

Multiple performance objectives in turn-mill multitasking machining are investigated using the Taguchi method combined with the fuzzy theory. Using these two methods, optimized processing parameters can be rapidly identified to obtain optimized dimensional accuracy and geometrical shape angle, thus reducing machining cost and time. Herein, control factors for determining the single objective optimization parameter using the Taguchi robust process L9(34) orthogonal table were spindle speed (rpm), feed (mm/min), C-axis brake pressure (kg/cm2), axial cutting depth (mm), with dimensional accuracy and geometrical shape angle as objective characteristics. Then, signal-to-noise ratios of different groups were generated by gray correlation according to the experimental sequence to obtain the gray correlation coefficient for the calculation of the multiple performance characteristic index (MPCI). The MPCI results demonstrated that optimized dimensional accuracy was 0.005 mm and optimized geometrical shape angle was 0.004°. The optimized MPCI parameters were A3 (4000 rpm), B3 (250 mm/min), C3 (30 kg/cm2), and D3 (1.5 mm). It can reduce the processing for burr elimination and tool wear reduction by MPCI optimized process parameters.

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