Bicycles are known to be rich source of kinetic energy, some of which is available for harvesting during speedy and balanced maneuvers by the user. A conventional dynamo attached to the rim can generate a large amount of output power at an expense of extra energy input from the user. However, when applying energy conversion technology to human powered equipments, it is important to minimize the increase in extra muscular activity and to maximize the efficiency of human movements. This study proposes a novel energy harvesting methodology that utilizes lateral oscillation of bicycle frame (weaving) caused by user weight shifting movements in order to increase the pedaling force in uphill riding or during quick speed-up. Based on the 3D motion analysis, we designed and implemented the prototype of an electro-dynamic energy harvester that can be mounted on the bicycle’s handlebar to collect energy from the side-to-side movement. The harvester was found to generate substantial electric output power of 6.6 mW from normal road riding. It was able to generate power even during uphill riding which has never been shown with other approaches. Moreover, harvesting of energy from weaving motion seems to increase the economy of cycling by helping efficient usage of human power.

We propose a data refinement and channel selection method for vapor classification in a portable e-nose system. For the robust e-nose system in a real environment, we propose to reduce the noise in the data measured by sensor arrays and distinguish the important part in the data by the use of feature feedback. Experimental results on different volatile organic compounds data show that the proposed data refinement method gives good clustering for different classes and improves the classification performance. Also, we design a new sensor array that consists only of the useful channels. For this purpose, each channel is evaluated by measuring its discriminative power based on the feature mask used in the data refinement. Through the experimental results, we show that the new sensor array improves both the classification rates and the efficiency in computation and data storage.

Power management systems (PMSs) are essential for the practical use of microbial fuel cell (MFC) technology, as they replace the unstable stacking of MFCs with step-up voltage conversion. Maximum-power extraction technology could improve the power output of MFCs; however, owing to the power consumption of the PMS operation, the maximum-power extraction point cannot deliver maximum power to the application load. This study proposes a practical power extraction for single MFCs, which reserves more electrical energy for an application load than conventional maximum power-point tracking (MPPT). When experimentally validated on a real MFC, the proposed method delivered higher output power during a longer PMS operation time than MPPT. The maximum power delivery enables more effective power conditioning of various micro-energy harvesting systems.

A small electronic nose (E-Nose) system has been developed using an 8-channel vapor detection array and personal digital assistant (PDA). The sensor array chip, integrated on a single microheater-embedded polyimide substrate, was made of carbon black-polymer composites with different kinds of polymers and plasticizers. We have successfully classified various volatile organic compounds such as methanol, ethanol, i-propanol, benzene, toluene, n-hexane, n-heptane, and c-hexane with the aid of the sensor array chip, and have evaluated the resolution factors among them, quantitatively. To achieve a PDA-based E-Nose system, we have also elaborated small sensor-interrogating circuits, simple vapor delivery components, and data acquisition and processing programs. As preliminary results show, the miniaturized E-Nose system has demonstrated the identification of essential oils extracted from mint, lavender, and eucalyptus plants.

The human-powered self-generator provides the best solution for individuals who need an instantaneous power supply for travel, outdoor, and emergency use, since it is less dependent on weather conditions and occupies less space than other renewable power supplies. However, many commercial portable self-generators that employ hand-cranking are not used as much as expected in daily lives although they have enough output capacity due to their intensive workload. This study proposes a portable human-powered generator which is designed to obtain mechanical energy from an upper limb pulling motion for improved human motion economy as well as efficient human-mechanical power transfer. A coreless axial-flux permanent magnet machine (APMM) and a flywheel magnet rotor were used in conjunction with a one-way clutched power transmission system in order to obtain effective power from the pulling motion. The developed prototype showed an average energy conversion efficiency of 30.98% and an average output power of 0.32 W with a maximum of 1.89 W. Its small form factor (50 mm × 32 mm × 43.5 mm, 0.05 kg) and the substantial electricity produced verify the effectiveness of the proposed method in the utilization of human power. It is expected that the developed generator could provide a mobile power supply.