Abstract
The purpose of this study was to explore a novel approach to power hybridization in relation to its effectiveness in an unmanned ground vehicle (UGV). This hybridization method is modeled after the power distribution methods found in living organisms, which utilize glycogen stores and adipose tissue to optimize power and energy density strengths and weaknesses. A UGV rover was constructed with an appropriate distribution of power storage elements creating separate power buffers. The primary buffer consisted of a 10Wsolar panel array and a 600 F, 5.4 V supercapacitor bank, and the secondary buffer consisted of a 3.7 V 6 Ah lithium-ion battery pack. The primary buffer provided virtually limitless charge cycles with a superior power density juxtaposed with a secondary buffer that provided superior energy density and volumetric versatility. The design of this rover is presented in this paper; it was tested under manual and autonomous modes. The rover was found to be capable of effectively operating solely on the primary power buffer in high to low luminous conditions while being able to carry out basic extravehicular activities. The rover could travel roughly 22 km without any input power on a full charge of both buffers, and could smoothly switch between its own power buffers during operation, all while transmitting live first person video (FPV) and network data. The introduction of control algorithms on the onboard microcontroller unit (MCU) was also explored in both manual and autonomous configurations. The latter integrated linear regression to intelligently manage power and locomotion based on sensory data from photoresistors.
Original language | English (US) |
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Article number | 6 |
Journal | Electronics (Switzerland) |
Volume | 7 |
Issue number | 1 |
DOIs | |
State | Published - Jan 2018 |
Keywords
- Exploration
- Hybridization
- Internet-of-Things
- Lithium-ion
- Machine-learning
- Perturb-and-observe
- Rover
- Solar
- Supercapacitors
- Unmanned-ground-vehicle
ASJC Scopus subject areas
- Control and Systems Engineering
- Signal Processing
- Hardware and Architecture
- Computer Networks and Communications
- Electrical and Electronic Engineering