BackgroundMuch research in the field of energy harvesting has sought to develop devices capable of generating electricity during daily activities with minimum user effort. No previous study has considered the metabolic cost of carrying the harvester when determining the energetic effects it has on the user. When considering device carrying costs, no energy harvester to date has demonstrated the ability to generate a substantial amount of electricity (> 5W) while maintaining a user effort at the same level or lower than conventional power generation methods (e.g. hand crank generator).Methodology/Principal FindingsWe developed a lower limb-driven energy harvester that is able to generate approximately 9W of electricity. To quantify the performance of the harvester, we introduced a new performance measure, total cost of harvesting (TCOH), which evaluates a harvester’s overall efficiency in generating electricity including the device carrying cost. The new harvester captured the motion from both lower limbs and operated in the generative braking mode to assist the knee flexor muscles in slowing the lower limbs. From a testing on 10 participants under different walking conditions, the harvester achieved an average TCOH of 6.1, which is comparable to the estimated TCOH for a conventional power generation method of 6.2. When generating 5.2W of electricity, the TCOH of the lower limb-driven energy harvester (4.0) is lower than that of conventional power generation methods.Conclusions/SignificanceThese results demonstrated that the lower limb-driven energy harvester is an energetically effective option for generating electricity during daily activities.

Evolutionary pressures have led humans to walk in a highly efficient manner that conserves energy, making it difficult for exoskeletons to reduce the metabolic cost of walking. Despite the challenge, some exoskeletons have managed to lessen the metabolic expenditure of walking, either by adding or storing and returning energy. We show that the use of an exoskeleton that strategically removes kinetic energy during the swing period of the gait cycle reduces the metabolic cost of walking by 2.5 ± 0.8% for healthy male users while converting the removed energy into 0.25 ± 0.02 watts of electrical power. By comparing two loading profiles, we demonstrate that the timing and magnitude of energy removal are vital for successful metabolic cost reduction.

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Biomechanical energy harvesters (BMEHs) have shown that useable amounts of electricity can be generated from daily movement. Where access to an electrical power grid is limited, BMEHs are a viable alternative to accommodate energy requirements for portable electronics. In this paper, we present the detailed design and dynamic model of a lower limb-driven energy harvester that predicts the device output and the load on the user. Comparing with existing harvester models, the novelty of the proposed model is that it incorporates the energy required for useful electricity generation, stored inertial energy, and both mechanical and electrical losses within the device. The model is validated with the lower limb-driven energy harvester in 12 unique configurations with a combination of four different motor and three different electrical resistance combinations (3.5 Ω, 7 Ω, and 12 Ω). A case study shows that the device can generate between 3.6 and 15.5 W with an efficiency between 39.8% and 72.5%. The model was able to predict the harvester output peak voltage within 5.6 ± 3.2% error and the peak force it exerts on the user within 9.9 ± 3.4% error over a range of parameter values. The model will help to identify configurations to achieve a high harvester efficiency and provide a better understanding of how parameters affect both the timing and magnitude of the load felt by the user.

This thesis discusses a power electronics module (PEM) that is used to extract power from a human energy harvesting generator according to the user's desired input power, and stores all of the extracted energy into an appropriately sized battery while staying within the charging limitations of the battery. The PEM can temporarily store the peak power produced by the generator allowing the reduction in the size of the battery required to the average power production level of the generator.The battery's safety and longevity is maintained by charging them at the constant current and constant voltage rate.The design of the two-stage PEM, the requirements of the Energy Storage Capacitor (ESC) and battery size are discussed. The two controllers that control the PEM are explained and the different operating modes of the controllers are reviewed. A two-stage prototype digitally controlled average current mode control Boost converter and average current mode controlled Buck converter were designed and experimental waveforms were captured to test and validate the control theories used in the PEM. A Voltage Adaptive Gain compensator was used to optimize the closed loop response of both the Boost and Buck converters over their respective output and input voltage ranges. The DC efficiency of the prototype was measured with the peak efficiency of the Boost converter equal to 93% and the peak efficiency of the Buck converter measured at 93.7%. The total PEM system efficiency was measured at 87.9% at an input power level of 10 watts. The AC efficiency of the PEM was also measured with a peak efficiency of 91% with V in = 15 V at R in = 60 Ω.The software considerations for an embedded system, including power consumption and timing of real time events are reviewed. A software flow chart and timing diagram are provided to help iii visualize the sequence of the code. A design chart for selection of the size and voltage rating of the ESC was created. An experimental comparison of a single stage design without energy storage capability and the current PEM design was performed, with a power limited source, in order to show the effectiveness of the PEM and controllers at maximizing the power extraction from the generator. The PEM design was able to extract 50% more power than the single stage converter without energy storage capability.iv Acknowledgements First of all I would like to thank not only my supervisor, but also my mentor through this process, Dr. Yan-Fei Liu. He has provided me with structure and encouragement throughout the duration of my degree. Secondly, I would like to give a special thanks to my partner in designing, prototyping, and testing of the human energy harvester. Michael Sherpertycky has been an excellent support as well as a good friend. I was also surrounded by great lab mates, who have become friends throughout the process, and offered valuable insight.