Improve the Energy Harvesting Alternatives Using the Bond Graph Approach for Powering Critical Autonomous Devices

Touairi, Souad; Mabrouki, Mustapha

doi:10.1007/978-3-030-73882-2_143

Cited by 5 publications

(1 citation statement)

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“…Conversely, however, batteries, which initially powered the growth of portable electronic devices, are now hampering further progress due to associated maintenance issues, such as recharging and replacement [6]. Although the performance of electric vehicle parts and subsystems improved substantially between 2003 and 2024, as demonstrated by the logarithmic scale [7], battery development has revealed its limitations [8]. In addition, scientists have highlighted the fact that battery technology is not evolving as dynamically as other electric vehicles.…”

Section: Introductionmentioning

confidence: 99%

Maximizing Electric Power Recovery through Advanced Compensation with MPPT Algorithms

Touairi,

Zekraoui,

Mabrouki

2024

Modelling and Simulation in Engineering

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The present investigation introduces an advanced methodology for maximum power point tracking (MPPT) applied to a piezo harvester scheme. A comprehensive rectifier circuit, equipped with an embedded MPPT component, is established to optimize energy production by monitoring a DC-DC inverter connected to the rectifier. Furthermore, the system’s sensitivity error has been finely tuned to dynamically adjust its impedance unit in real time, thereby optimizing load acquisition. This innovative approach seamlessly integrates the MPPT algorithm into the piezo harvester circuit. Moreover, the vehicle’s road handling is significantly augmented through the incorporation of a robust steering front and an active differential control system. Leveraging the MPPT module, the rectifier consistently achieves a power recovery efficiency exceeding 85%, independent of varying load conditions. Additionally, a DC-DC converter circuit has been seamlessly integrated to finely adjust the output voltage to meet specified levels. Numerical simulations demonstrate the effectiveness of the harvesting scheme, extracting a substantial output power of 90 W with an overall efficiency of 70%. The improved MPPT approach, employing angles of arrival (AoA) DV-Hop control strategies, minimizes the system’s power consumption based on the Global Positioning System (GPS). The utilization of Harris Hawks optimization (HHO) and the generation of quadrants in the four-quadrant operation mode of DC motors in the wireless sensor network (RCSFs) have been significantly enhanced in this study. Simulations reveal that, at a velocity of 50 km/h, shock absorbers utilizing the received signal strength indication (RSSI) can harvest between 60 and 90 W on a class C road, based on the time of arrival (TOA). Striking a balance in ride comfort using the time difference of arrival (TDOA) as a trade-off constitutes approximately 30% of the piezoelectric harvester (PEH) system’s power consumption when operating in active suspension mode, optimized by particle swarm optimization (PSO).

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Section: Introductionmentioning

confidence: 99%