• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.9
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• pp.1669-1673
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• 2008

A new cycle ergometer using a Magneto-Rheological (MR) rotary brake system has been developed for rehabilitation of hemiplegia patients to reduce uneven pedaling characteristics. For this purpose, a control method to adjust the resistance of the MR rotary brake in real time based on the magnitude of the muscular force exerted by the subject has been devised so that the mechanical resistance to the pedaling can be minimized when the affected leg was engaged for pedaling. A series of experiments were carried out with and without the engagement of this real-time control mode of MR rotary brake at different pedaling rate to find out the effect of the real-time control mode. The characteristics of the pedaling for these specific conditions were analyzed based on the variations in angular velocities of the pedal unit. The results showed that the variations in the angular velocities were decreased by 42.9% with the control mode. The asymmetry of pedaling between dominant and non-dominant leg was 19.63% in non-control mode and 1.97% in the control mode. The characteristics of electromyography(EMG) in the lower limbs were also measured. The observation showed that Integrated EMG(IEMG) reduced with the control mode. Therefore, the new bicycle system using MR brake with the real time control of mechanical resistance was found to be effective in recovering the normal pedaling pattern by reducing unbalanced pedaling characteristics caused by disparity of muscular strength between affected and unaffected leg.

• Journal of Digital Convergence
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• v.17 no.11
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• pp.207-213
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• 2019

The fuel-cut coast-down driving mode is activated when the acceleration pedal is released with transmission gear engaged, and it's a default function for electronic-controlled engine of vehicles. The fuel economy becomes better because fuel injection stops during fuel-cut driving mode. A fuel-cut detection method is suggested in the study and it's based on the speed, acceleration and road gradient data from GPS sensor. It detects fuel-cut driving mode by comparing calculated acceleration and realtime acceleration value. The one is estimated with driving resistance in the condition of fuel-cut driving and the other is from GPS sensor. The detection accuracy is about 80% when the method is verified with road driving data. The result is estimated with 9,600 data set of vehicle speed, acceleration, fuel consumption and road gradient from test driving on the road of 12km during 16 minutes, and the road slope is rather high. It's easy to detect fuel-cut without injector signal obtained by connecting wire. The detection error is from the fact that the variation range of speed, acceleration and road gradient data, used for road resistance force, is larger than the value of fuel consumption data.