A Review of Energy Management Strategies for Hybrid Electric Vehicles
This review systematically categorizes energy management strategies (EMS) for hybrid electric vehicles, highlighting rule‐based, optimization‐based, learning‐based, and emerging algorithm‐mixing approaches. It provides a comprehensive roadmap for developing intelligent control systems to enhance energy efficiency and promote sustainable transportation.
Song Gao +9 more
wiley +1 more source
Multi-layer and multi-channel deposition defects and inter-layer control strategies in additive manufacturing materials. [PDF]
Sun W, Li M.
europepmc +1 more source
Duckworth-Lewis-Stern modeling with fuzzy logic and contextual indices for target revision in cricket. [PDF]
Samanta S +3 more
europepmc +1 more source
Development of a Neural-Fuzzy-Based Variable Admittance Control Strategy for an Upper Limb Rehabilitation Exoskeleton. [PDF]
Shi Y, Li K, Zhang Y, Wu Q.
europepmc +1 more source
Federated TriNet-AQ: Explainable english proficiency classification in augmented and virtual reality learning. [PDF]
Zhang C, Liu Z.
europepmc +1 more source
Fuzzy logic-based reactive power control for power factor enhancement in EV drives. [PDF]
Mohan H +6 more
europepmc +1 more source
Explainable gradient convolutional vector fuzzy pattern analysis based on ensemble model for facial expression recognition. [PDF]
Videla LS, Mukamalla BR.
europepmc +1 more source
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Fuzzy logic in control systems: fuzzy logic controller. I
IEEE Transactions on Systems, Man, and Cybernetics, 1990For pt.I see ibid., vol.20, no.2, p.404-18, 1990. The basic aspects of the FLC (fuzzy logic controller) decision-making logic are examined. Several issues, including the definitions of a fuzzy implication, compositional operators, the interpretations of the sentence connectives 'and' and 'also', and fuzzy inference mechanisms, are investigated ...
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A fuzzy logic framework is proposed to alleviate two problems in traditional CBIR systems, including the semantic gap and the perception subjectivity. The proposed framework consists of two major parts, including (1) model construction and (2) query comparison.
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