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The purpose of this paper is to propose a new outer‐rotor permanent‐magnet flux‐switching machine (ORPMFSM) for electric vehicle (EV) in‐wheel propulsion. The paper documents both the design procedure and performance investigation of this novel machine.

The topology and preliminary sizing equations of the ORPMFSM are introduced. The rotor poles are optimized, whilst the machine losses are particularly investigated, using 2‐D finite element analysis (FEA).

An ORPMFSM, with 12 stator poles and 22 rotor poles, is most suitable for the proposed EV application. The analytical sizing equations are quite efficient with a sufficient accuracy for the preliminary design. The optimal rotor pole width from the FEA results is nearly 1.3 times the original value which was proposed in early literatures. The efficiency of the proposed machine under rated load is slightly low, as a result of significant eddy current losses in the permanent magnets. The losses can be effectively suppressed with the technique of magnet segmenting. The predicted outstanding performance implies that by adopting magnet segmentation the proposed machine is a leading contender for EV direct drives.

The outer‐rotor structure of PMFSM was not addressed in early literatures. This paper provides designers with the technical background and an alternative candidate for the EV propulsion.

The purpose is to present a sensorless control method by which high‐resolution rotor position information is estimated and used for phase‐advancing operation of a high‐speed permanent magnet (PM) brushless DC (BLDC) motor.

The proposed sensorless control approach uses hardware to observe the flux vector which is excited by rotor magnets. It can provide the rotor position which is the same as the phase angle of the observed flux vector.

High‐resolution rotor position signal of the BLDC motor for dynamic phase‐advancing control cannot be directly obtained from the conventional Hall‐effect sensors, or via the traditional back‐EMF‐based sensorless control strategies in which the back‐EMF may be even undetectable at high‐speed. The proposed rotor‐flux‐observer (RFO)‐based sensorless control method overcomes these problems, and meanwhile provides high‐resolution rotor position information for the phase‐advancing purpose.

The RFO‐based sensorless control is traditionally applied to PM brushless ac (BLAC) operations, where the motor voltage vector can be calculated from the inverter switching status. However, this is not readily applicable to a BLDC motor since the voltage of the floating phase cannot be calculated. Moreover, during high‐speed operation, the microprocessor may not be sufficiently fast to calculate the high‐resolution rotor position. Therefore, in this paper, it is proposed to use hardware to observe the rotor‐flux‐vector. The microprocessor only samples the vector's α‐ and β‐components and calculates the phase angle, hence, its burden is low. The proposed method is validated with a 1.8 kW 85,000 rpm BLDC motor system.

Studies on cross-culture marketing often focus on either localization or globalization strategies. Based on data from pre-communist China (1912–1949), product hybridization – defined as a process or strategy that generates symbols, designs, behaviors and cultural identities that blend local and global elements – emerges as a popular intermediate strategy worthy of further inquiry. After examining the mechanisms and processes underlying this strategy, a schema for classifying product hybridization strategies is developed and illustrated. The paper aims to discuss these issues.

Critical historical research method is applied to historical data and historical “traces” from pre-communist China’s corporate documents, memoirs, posters, advertisements, newspapers and secondhand sources.

Strategic interactions between domestic and foreign companies in pre-communist China fostered products and a city (Shanghai) containing Chinese and non-Chinese elements. Informed by historical traces and data from pre-communist China (1912-1949), a 2 × 2 classification schema relating company type (i.e. foreign or domestic) to values spectrum endpoint (i.e. domestic vs foreign) was formulated. This schema reflects the value of communication, negotiation and cultural (inter)penetration that accompanies cross-culture product flows.

Cross-culture marketing strategies meant to help companies satisfy diverse marketplace interests can induce a mélange of product design elements. Because product hybridization reflects reciprocity between domestic and foreign companies that embodies multiple interests and contrasting interpretations of product meanings, researchers should examine globalization and localization synergistically.

Strategies adopted by domestic and foreign companies in pre-communist China (1912–1949) can help contemporary companies design effective cross-culture marketing strategies in a global marketplace infused with competing meanings and interests.

Examining historical strategies adopted in pre-communist China (1912–1949) can inform contemporary marketers’ intuitions. Understanding product hybridization in global marketplaces can improve marketing efficiency.

Visual tracking technology enables industrial robots interacting with human beings intelligently. However, due to the complexity of the tracking problem, the accuracy of visual target tracking still has great space for improvement. This paper aims to propose an accurate visual target tracking method based on standard hedging and feature fusion.

For this study, the authors first learn the discriminative information between targets and similar objects in the histogram of oriented gradients by feature optimization method, and then use standard hedging algorithms to dynamically balance the weights between different feature optimization components. Moreover, they penalize the filter coefficients by incorporating spatial regularization coefficient and extend the Kernelized Correlation Filter for robust tracking. Finally, a model update mechanism to improve the effectiveness of the tracking is proposed.

Extensive experimental results demonstrate the superior performance of the proposed method comparing to the state-of-the-art tracking methods.

Improvements to existing visual target tracking algorithms are achieved through feature fusion and standard hedging algorithms to further improve the tracking accuracy of robots on targets in reality.