A hybrid kinetic energy harvester for applications in electric driverless buses

Tang, Minfeng; Cao, Hao; Kong, Lingji; Azam, Ali; Luo, Dabing; Pan, Yajia; Zhang, Zutao

doi:10.1016/j.ijmecsci.2022.107317

Cited by 34 publications

(11 citation statements)

References 50 publications

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“…This unbalanced mechanism couples chaotic motion to the transducer and is more suitable for random irregular, low-frequency motion. [78][79][80] The output performance of EMEH is primarily influenced by two critical components, namely, permanent magnets and coils. [81,82] The magnet material properties directly impact the energy conversion efficiency.…”

Section: Electromagneticmentioning

confidence: 99%

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Harvesting Inertial Energy and Powering Wearable Devices: A Review

Zhang,

Shen,

Zheng

et al. 2023

Small Methods

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Amidst the swift progression of microelectronics and Internet of Things technology, wearable devices are gradually gaining ground in the domains of human health monitoring. Recently, human bioenergy harvesting has emerged as a plausible alternative to batteries. This paper delves into harvesting human inertial energy that stimulates inertial masses through human motion and then transmutes the motion of the inertial masses into electrical energy. The inertial energy harvester is better suited for low‐frequency and irregular human motion. This review first identifies the sources of human motion excitation that are compatible with inertial energy harvesters and then provides a summary of the operating principles and the comparisons of the commonly used energy conversion mechanisms, including electromagnetic, piezoelectric, and triboelectric transducers. The review thoroughly summarizes the latest advancements in human inertial energy‐harvesting technology that are categorized and grouped based on their excitation sources and mechanical modulation methods. In addition, the review outlines the applications of inertial energy harvesters in powering wearable devices, medical health monitoring, and as mobile power sources. Finally, the challenges faced by inertial energy‐harvesting technologies are discussed, and the review provides a perspective on the potential developments in the field.

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Section: Electromagneticmentioning

confidence: 99%

“…This unbalanced mechanism couples chaotic motion to the transducer and is more suitable for random irregular, low‐frequency motion. [ 78–80 ]…”

Section: System Framework Excitation Sources and Energy Conversion Me...mentioning

confidence: 99%

Harvesting Inertial Energy and Powering Wearable Devices: A Review

Zhang,

Shen,

Zheng

et al. 2023

Small Methods

Self Cite

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“…The advent of Artificial Intelligence (AI) and Internet of Things (IoT) technologies has led to notable developments in the realm of wearable electronic devices. [ 1,2 ] On the one hand, with the help of energy harvesting technology, [ 3,4 ] it is very potential for these electronic devices to harvest human body energy (kinetic energy, [ 5,6 ] thermal energy, [ 7,8 ] and biochemical energy [ 9 ] ), and environmental energy (solar energy, [ 10 ] and radio frequency energy [ 11 ] ). On the other hand, with self‐powered sensing technology, [ 12–15 ] these electronic devices play a huge role in healthcare, [ 16 ] rehabilitation training, [ 17 ] sports monitoring, [ 18 ] disease diagnosis, [ 19 ] etc.…”

Section: Introductionmentioning

confidence: 99%

A Self‐Powered and Self‐Sensing Lower‐Limb System for Smart Healthcare

Kong

Fang

Zhang

et al. 2023

Advanced Energy Materials

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In the age of the artificial intelligence of things (AIoT), wearable devices have been extensively developed for smart healthcare. This paper proposes a self‐powered and self‐sensing lower‐limb system (SS‐LS) with negative energy harvesting and motion capture for smart healthcare. The SS‐LS achieves self‐sustainability via a half‐wave electromagnetic generator (HW‐EMG) that recovers negative work from walking with a low cost of harvesting. Additionally, the motion capture function of the system is achieved by the three‐channel triboelectric nanogenerator (TC‐TENG) based on binary code, which can accurately detect the angle and direction of the knee joint rotation. The bench test experiment indicates that the HW‐EMG has an average output power of 11.2 mW, sufficient to power a wireless sensor. The three‐channel voltage signal of TC‐TENG fits well with the binary signal, which can precisely detect the angle and direction of rotation. Furthermore, the SS‐LS demonstrates an identification accuracy of 99.68% and a motion detection accuracy of 99.96% based on an LSTM deep learning model. Demonstrations of Parkinson's disease and fall detection and monitoring of three training modes (sit‐and‐stand, balance, and walking training) are also performed, which exhibit outstanding sensing capabilities. The SS‐LS is highly promising in sports rehabilitation medicine and can contribute to the development of smart healthcare.

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“…[62][63][64] In addition to the micro-energy sources mentioned above, mechanical energy is also a widely distributed renewable microenergy, including vibration energy that exists in automobile suspensions, [65] rails, [66] and machines, [67] ubiquitous wind energy in the air, [68,69] wave energy in oceans and rivers, [70,71] biomechanical energy in human and animal motion, [72][73][74] sound energy in traffic environments and cities. [75,76] Moreover, mechanical energy can be converted into electrical energy through various mechanisms, such as piezoelectric, [77] triboelectric, [78] electromagnetic, [79] electrostatic, [80] and magnetostrictive. [81] In recent years, wearable mechanical energy harvesting devices integrated into the human body have been extensively studied.…”

Section: Introductionmentioning

confidence: 99%

Recent Progress in Application‐Oriented Self‐Powered Microelectronics

Qi,

Kong,

Wang

et al. 2023

Advanced Energy Materials

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With the rapid development of the Internet of Things (IoTs), numerous distributed wide‐area low‐power electronic devices have been utilized in various fields, such as wireless monitoring sensors and wearable electronics. Due to the dispersion and mobility of microelectronic devices, their energy supply faces serious challenges. The inconvenience and non‐environmental friendliness of using traditional centralized low entropy energy and chemical batteries to power distributed microelectronic devices are becoming increasingly prominent. Environmental energy harvesting technology with high entropy characteristics is considered an effective solution for low‐power electronic devices. This paper comprehensively reviews the recent progress in microelectronic technologies based on energy harvesting and signal sensing. First, state‐of‐the‐art micro‐power electronic devices in humans, animals, and the environment are introduced. Secondly, the available micro‐energy sources in the environmentare elaborated and summarized. Then, the principles and characteristics of ambient microenergy harvesting technologies based on different mechanisms are classified, summarized, and analyzed. In addition, this work comprehensively summarizes the applications of self‐powered micro‐electronics technology in 11 different fields, including human, animal, and environment. Finally, research challenges, technical difficulties, and research gaps in self‐powered microelectronics based on micro‐energy harvesting technology are discussed and summarized.

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A hybrid kinetic energy harvester for applications in electric driverless buses

Cited by 34 publications

References 50 publications

Harvesting Inertial Energy and Powering Wearable Devices: A Review

Harvesting Inertial Energy and Powering Wearable Devices: A Review

A Self‐Powered and Self‐Sensing Lower‐Limb System for Smart Healthcare

Recent Progress in Application‐Oriented Self‐Powered Microelectronics

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