Model-Based Fault Detection of Permanent Magnet Synchronous Motors of Drones Using Current Sensors

PurposeThis study presents a systematic literature review (SLR) of the interdisciplinary literature on drones in last-mile delivery (LMD) to extrapolate pertinent insights from and into the logistics management field.Design/methodology/approachRooting their analytical categories in the LMD literature, the authors performed a deductive, theory refinement SLR on 307 interdisciplinary journal articles published during 2015–2022 to integrate this emergent phenomenon into the field.FindingsThe authors derived the potentials, challenges and solutions of drone deliveries in relation to 12 LMD criteria dispersed across four stakeholder groups: senders, receivers, regulators and societies. Relationships between these criteria were also identified.Research limitations/implicationsThis review contributes to logistics management by offering a current, nuanced and multifaceted discussion of drones' potential to improve the LMD process together with the challenges and solutions involved.Practical implicationsThe authors provide logistics managers with a holistic roadmap to help them make informed decisions about adopting drones in their delivery systems. Regulators and society members also gain insights into the prospects, requirements and repercussions of drone deliveries.Originality/valueThis is one of the first SLRs on drone applications in LMD from a logistics management perspective.

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Model-Based Fault Detection of Permanent Magnet Synchronous Motors of Drones Using Current Sensors

Cited by 5 publications

References 5 publications

Chaos Control of BLDC Motor via Fuzzy Based PID Controller

Chaos Control of BLDC Motor via Fuzzy Based PID Controller

Drones for supply chain management and logistics: a review and research agenda

Drones in last-mile delivery: a systematic literature review from a logistics management perspective

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