Extremely low frequency (ELF) magnetic field (MF) exposure in electric vehicles (EVs) has raised public concern for human health. There have been many studies evaluating magnetic field values in these vehicles. However, there has been no report on the temporal variation of the magnetic field in the cabin. This is the first study on the long-term monitoring of actual MFs in EVs. In the study, we measured the magnetic flux density (B) in three shared vehicles over a period of two years. The measurements were performed at the front and rear seats during acceleration and constant-speed driving modes. We found that the B amplitudes and the spectral components could be modified by replacing the components and the hubs, while regular checks or maintenance did not influence the B values in the vehicle. This observation highlights the necessity of regularly monitoring ELF MF in EVs, especially after major repairs or accidents, to protect car users from potentially excessive ELF MF exposure. These results should be considered in updates of the measurement standards. The ELF MF effect should also be taken into consideration in relevant epidemiological studies.

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Abstract. The shift logic of most automatic shift systems is based on two parameters-vehicle speed and throttle opening. In this paper, two-parameter shift schedule is applied for AT. The shift logic is on the basis of the optimal efficiency of the motor-transmission system. The model is built by Simulink/Stateflow and the simulation is carried up based on the driving cycle. Driving economy can be improved significantly after applying this shift logic for the power system.

In the electric vehicles (EVs), children can sit on a safety seat installed in the rear seats. Owing to their smaller physical dimensions, their heads, generally, are closer to the underfloor electrical systems where the magnetic field (MF) exposure is the greatest. In this study, the magnetic flux density (B) was measured in the rear seats of 10 different EVs, for different driving sessions. We used the measurement results from different heights corresponding to the locations of the heads of an adult and an infant to calculate the induced electric field (E-field) strength using anatomical human models. The results revealed that measured B fields in the rear seats were far below the reference levels by the International Commission on Non-Ionizing Radiation Protection. Although small children may be exposed to higher MF strength, induced E-field strengths were much lower than that of adults due to their particular physical dimensions.

At present, the prevalence of electric vehicles is increasing continuously. In particular, there are promising applications for commercial vehicles transfering from conventional to full electric, due to lower operating costs and stricter emission regulations. Thus, cost analysis from the fleet perspective becomes important. The study of cost competitiveness of different drivetrain designs is necessary to evaluate the fleet cost variance for different degrees of electrical machine commonality. This paper presents a methodology to find a preliminary powertrain design that minimizes the Total Cost of Ownership (TCO) for an entire fleet of electric commercial vehicles while fulfilling the performance requirements of each vehicle type. This methodology is based on scalable electric machine models, and particle swarm is used as the main optimization algorithm. The results show that the total cost penalty incurred when sharing the same electrical machine is small, therefore, there is a cost saving potential in higher degrees of electrical machine commonality.