SAE Technical Paper Series 2004
DOI: 10.4271/2004-01-3166
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Performance Characterization of a Lithium-Ion Gel Polymer Battery Power Supply System for an Unmanned Aerial Vehicle

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Cited by 7 publications
(4 citation statements)
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“…The form of the curves suggests that increasing effective capacity benefits both range and endurance stemming from the Peukert effect but to a lesser relative extent as C increases (observe the decreasing slope of the curves). Note that effective battery capacity is also dependent on temperature, such that increasing temperature (within bounds) generally improves capacity [9]. Figure 1 is indicative of the impact of improved battery technology, allowing greater capacity for a fixed battery weight.…”
Section: Theoretical Developmentmentioning
confidence: 97%
See 1 more Smart Citation
“…The form of the curves suggests that increasing effective capacity benefits both range and endurance stemming from the Peukert effect but to a lesser relative extent as C increases (observe the decreasing slope of the curves). Note that effective battery capacity is also dependent on temperature, such that increasing temperature (within bounds) generally improves capacity [9]. Figure 1 is indicative of the impact of improved battery technology, allowing greater capacity for a fixed battery weight.…”
Section: Theoretical Developmentmentioning
confidence: 97%
“…This value is then used in Eq. (9). To estimate the maximum range, the required velocity is determined using Eq.…”
Section: Theoretical Developmentmentioning
confidence: 99%
“…In summary, many of these propulsion systems, which are unique to unmanned aerial vehicle systems, are not traditionally considered to be present at the present regulatory standards. It is largely due to the unique operational objectives of the unmanned aerial system with specific mission requirements that are significantly different from human aviation [13]. Piston engines and electric engines are the most commonly used types.…”
Section: Resultsmentioning
confidence: 99%
“…Traditional fault detection methods mainly rely on the experience of power workers and manual inspection, which is not only time-consuming, but also easy to miss detection, which seriously affects the timeliness of fault response. Therefore, the introduction of automatic feature extraction has become an important means to improve the efficiency and accuracy of fault detection [7].…”
Section: Application Of Deep Learning In Fault Detectionmentioning
confidence: 99%