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This paper presents a analytical model for calculating the electromagnetic parameter of slotless permanent magnet (PM) motors. The load magnetic field in the machine can be divided in two parts: the magnetic field produced by PM, the magnetic field produced by winding current. Two analytical models are deduced separately based on the Maxwell's equations. The load magnetic field obtained ultimately using the superposition theorem. The electromagnetic parameter such as electromotive force (EMF) and torque are calculated based on the solution of the magnetic field. The test results verified the accuracy of the analytical model.

This paper deals with a permanent magnet synchronous generator (PMSG) used for integrated starter generator (ISG) in an urban compact extended-ranger electric vehicles (ER-EVs). Based on the special characteristics of ER-EVs, defined the power demanded of extended-ranger and discussed the design requirement and specification of generator. According to the given requirement of design, an optimizing routine is developed using simplified analytical calculation for finding optimal design of PMSG. The analytical calculation results are validated by FE simulation and proto type test.

The method to optimize the design of Permanent Magnet Synchronous Motor (PMSM) to solve irreversible permanent magnet demagnetization is discussed in this paper. A PMSM with rated speed 9000r/min and rated power 200 kW is used as origin model. The models except original one in this paper are designed by changing structure and parameters. The design of PMSM with lower eddy current loss of permanent magnet will be given by simulation and comparison of different models.

Reduction of permanent magnet materials is of interest to many designers as cost of rare earth increasing. In the paper, it is studied 20 % reduction of magnet size by optimizing shape of the magnets in Interior Permanent Magnet Synchronous Motor (IPMSM) and the aims to maintain the high efficiency map over the operating region. Finally, the Finite Element Method (FEM) Simulation result is verified by the testing.

Accurate short-term traffic flow forecasting is one of the important issues for intelligent transportation systems research, especially for the advanced traffic management systems and advanced traveler information systems research. With the shortening of the forecasting term, the uncertainty of traffic flow becomes more and more seriously, so that the forecasting effect of general approaches is decreasing. For an example, the algorithm based on non-parametric regression is a real-time nonparametric forecasting algorithm with the characteristic of high transplantation and accuracy, which plays an important role in traffic flow forecasting, yet there is the problem of "dimension curse" as the dimensions of the sample data increase. For the purpose of solving the question of short-time traffic flow forecasting, a short-time traffic flow forecasting model based on projection pursuit auto-regression technique is established in this paper. The problem of "dimension curse" and non-normality among high-dimensions data are solved. This algorithm satisfies the need of real-time traffic flow forecasting completely through the field data test

Aiming at the uncertainty of driving behavior, a new integrated cognitive car-following model to reflect the driver's psycho-physic characteristics is established in this paper. The model is calibrated with the field data collected by "Five-Wheel experiment System" and the multistatistical analysis method. Data different from what is used in the calibrated procedure is brought to validate the model. The results indicate that the model is very effective to reflect the complexity of the driving behavior, and reproduce the real dynamic procedure of the driver-car unit. The model and the algorithm can be provided as the theoretic basis of the integrated cooperated traffic network simulation and the intelligent transportation systems research.

Study of driving behavior is the important content of the Intelligent Transportation Systems and the theoretic basis of the microscopic traffic flow simulation. In the past, the research concerning to driving behavior mainly focused on the car-following process. From the view of the behavior analysis, the car-following models concerning to the human factors based on cybernetics are reviewed in this paper, such as the GHR model, the collision avoidance model, the AP model, the fuzzy logic model, the neural network model, and the desired headway model, and so on. During the establishment, the advantage and the disadvantage are discussed in detail. Some important questions used to characterize the driving behavior, which are usually ignored in the establishment process of the models, are also revealed. With the latest research of the modern traffic field, the development tendency of the driving behavior simulation models in the future is forecasted from the specialization of the application field, the diversification of the study means and the practicability of the model establishment.

The breakdown of traffic flow is directly related with the abnormal phenomena such as road traffic incidents. It results in the discontinuities of traffic and reduces the service level. The research of traffic flow breakdown is often narrowly confined to incident detection, and there are approximately 4 kinds of algorithms: pattern recognition algorithm, statistical inference algorithm, catastrophic theory and neural network algorithm. These methods have played important roles in their past applications, and each has shortcomings. This paper introduces a nonlinear and nonparametric statistical method to analyze traffic flow breakdown. Based on traffic flow theory and combined with mean-value change-point model, the hypothesis testing of the existence of change points and the local-comparison algorithm to search change-points are discussed. The method is calibrated with the data from the city of Southampton, UK. An example of the applications is also included to test the effectiveness of the method.

The lane utilization ratio reflects the traffic distribution on different lanes of road section for a single direction. It influences the stability of traffic flow, and is the important influential factor of road capacity and security. Aiming at the uncertainty of the lane utilization ratio and the difficulty to collect the field data under different volumes, in this paper, the research is carried out with microscopic traffic simulation model of car-following and lane-changing to study the basic rules of the lane utilization ratio/lane-changing times and the lane utilization ratio/traffic volume of the road section with two carriageways or three carriageways.