Robust multi‑objective transverse flux machine drive optimization considering torque ripple and manufacturing uncertainties

Yanbin Li,Heng Jia,Aijun Zhang,Bing Xiao,Yongsheng Zhu,Tingting Wei 전력전자학회 2023 JOURNAL OF POWER ELECTRONICS Vol.23 No.6

This paper presents a multi-objective robust optimization method for a drive system consisting of a permanent magnet transverse flux machine with soft magnetic composite cores and a field-oriented controller. Unlike existing research work, the torque ripple is considered an optimization objective. Several machine uncertainties caused by manufacturing tolerances are investigated in the robust optimization model under the framework of the design for six-sigma. Since this is a system-level optimization problem, two approximation models are employed to decrease the computational cost. First, a Kriging model is used to approximate the steady-state electromagnetic performances of the motor, such as the output power and efficiency. Second, a Taylor series approximation is employed to estimate the dynamic performances of the control system, such as the speed overshoot and settling time. Furthermore, a sampling selection method is proposed to reduce the computational cost of the Monte Carlo analysis in robust optimization. To show the eff ectiveness of the proposed method, both deterministic and robust Pareto solutions are presented and discussed. It can be seen that the system-level multi-objective design optimization based on robust approach can produce optimal Pareto solutions with a high manufacturing quality for the whole drive system. This is valuable for the batch production of electrical drive systems.

Microstructural Abnormalities of Basal Ganglia and Thalamus in Bipolar and Unipolar Disorders: A Diffusion Kurtosis and Perfusion Imaging Study

Lianping Zhao,Ying Wang,Yanbin Jia,Shuming Zhong,Yao Sun,Zhifeng Zhou,Zhongping Zhang,Li Huang 대한신경정신의학회 2017 PSYCHIATRY INVESTIGATION Vol.14 No.4

Objective: Bipolar disorder (BD) is often misdiagnosed as unipolar depression (UD), leading to mistreatment and poor clinical outcomes. However, little is known about the similarities and differences in subcorticalgray matter regions between BD and UD. Methods: Thirty-five BD patients, 30 UD patients and 40 healthy controls underwent diffusional kurtosis imaging (DKI) and three dimensional arterial spin labeling (3D ASL). The parameters including mean kurtosis (MK), axial kurtosis (Ka), radial kurtosis (Kr), fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (Da), radial diffusivity (Dr) and cerebral blood flow (CBF) were measured by using regions-of-interest analysis in the caudate, putamen and thalamus of the subcortical gray matter regions. Results: UD exhibited differences from controls for DKI measures and CBF in the left putamen and caudate. BD showed differences from controls for DKI measures in the left caudate. Additionally, BD showed lower Ka in right putamen, higher MD in right caudate compared with UD. Receiver operating characteristic analysis revealed the Kr of left caudate had the highest predictive power for distinguishing UD from controls. Conclusion: The two disorders may have overlaps in microstructural abnormality in basal ganglia. The change of caudate may serve as a potential biomarker for UD.

Nolinear Multi-component Spectroscopy Analysis Based on Evolutionary Construction Optimazation

Boyan Cai,Hui Cao,Yanbin Zhang,Lixin Jia,Gangquan Si,Zhongjian Li 제어로봇시스템학회 2015 제어로봇시스템학회 국제학술대회 논문집 Vol.2015 No.10

Spectroscopy has been widely used to evaluate product quality or to predict components. To deal with the nonlinearity of spectral data, artificial neural networks (ANN) are widely used. One weakness of ANN is we have no accurate analytical method to design a optimal network structure. A multivariate component prediction method based on optimized neural network combined with evolutionary algorithm (EA) for spectral analysis is proposed in the paper. For the proposed method, ANNs are combined with nonlinear adaptive evolutionary programming algorithm (NAEP) to evolve ANNs architecture including the number of hidden nodes and the number of hidden layers. And the root-meansquares error of cross-validation (RMSECV) is the fitness function of NAEP. In order to present the effectiveness of this method, back propagation neural network (BP) and ANN with genetic algorithm (ANN-GA) methods were also used for component predicting models. An application research has been demonstrated with spectral data which is recorded in an experiment of meat content determination. Results indicate that our method has the ability to design the best ANN structure to predict more accurate and robust as a practical spectral analysis tool.

Investigation into Engineering Ceramics Grinding Mechanism and the Influential Factors of the Grinding Force

DongKun Zhang,Changhe Li,Dongzhou Jia,Yanbin Zhang 보안공학연구지원센터 2014 International Journal of Control and Automation Vol.7 No.4

Convective Heat Transfer Coeicient Model Under Nanoluid Minimum Quantity Lubrication Coupled with Cryogenic Air Grinding Ti–6Al–4V

Jianchao Zhang,Wentao Wu,Changhe Li,Min Yang,Yanbin Zhang,Dongzhou Jia,Yali Hou,Runze Li,Huajun Cao,Hafiz Muhammad Ali 한국정밀공학회 2021 International Journal of Precision Engineering and Vol.8 No.4

Under the threat of serious environmental pollution and resource waste, sustainable development and green manufacturing have gradually become a new development trend. A new environmentally sustainable approach, namely, cryogenic air nanofluid minimum quantity lubrication (CNMQL), is proposed considering the unfavorable lubricating characteristic of cryogenic air (CA) and the deficient cooling performance of minimum quantity lubrication (MQL). However, the heat transfer mechanism of vortex tube cold air fraction by CNMQL remains unclear. The cold air fraction of vortex tubes influences the boiling heat transfer state and cooling heat transfer performance of nanofluids during the grinding process. Thus, a convective heat transfer coefficient model was established based on the theory of boiling heat transfer and conduction, and the numerical simulation of finite difference and temperature field in the grinding zone under different vortex tube cold air fractions was conducted. Simulation results demonstrated that the highest temperature initially declines and then rises with increasing cold air fraction. Afterward, this temperature reaches the lowest peak (192.7 °C) when the cold air fraction is 0.35. Experimental verification was conducted with Ti–6Al–4V to verify the convective heat transfer coefficient model. The results concluded that the low specific grinding energy (66.03 J/mm 3 ), high viscosity (267.8 cP), and large contact angle (54.01°) of nanofluids were obtained when the cold air fraction was 0.35. Meanwhile, the lowest temperature of the grinding zone was obtained (183.9 °C). Furthermore, the experimental results were consistent with the theoretical analysis, thereby verifying the reliability of the simulation model.

Effects of Physicochemical Properties of Different Base Oils on Friction Coefficient and Surface Roughness in MQL Milling AISI 1045

Qingan Yin,Changhe Li,Lan Dong,Xiufang Bai,Yanbin Zhang,Min Yang,Dongzhou Jia,Runze Li,Zhan-qiang Liu 한국정밀공학회 2021 International Journal of Precision Engineering and Vol.8 No.6

Minimum quantity lubrication (MQL) is an emerging green and resource-saving machining technique jetting minute amount lubricants and gas after mixing and atomization. However, MQL development is restricted to mineral oils because of its undegradability and threat to the environment and human health. Vegetable oils can replace mineral oils as base oil for MQL benefitting from its biodegradability and renewable property. Nevertheless, the lubrication mechanism at the tool-workpiece interface of different vegetable oils with various physicochemical properties has not been revealed systematically. In order to verify the interfacial lubrication characteristics of different vegetable oils, MQL milling experiments of AISI 1045 based on fi ve vegetable oils (cottonseed, palm, castor, soybean, and peanut oils) were carried out. The experimental results showed that, palm oil obtained the lowest milling force ( F x = 312 N, F y = 156 N), friction coeffi cient (0.78), and surface roughness values ( Ra = 0.431 μm, RSm = 0.252 mm) and the smoothest surface of workpiece. Furthermore, the physiochemical properties (composition, molecular structure, viscosity, surface tension, and contact angle) of vegetable oil were analyzed. Palm oil with high content of saturated fatty acid, high viscosity and small contact angle can form the lubricating oil fi lm with the highest strength and the largest spreading area at the tool-workpiece interface. Therefore, palm oil can achieve the optimal lubrication effect.