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@article{185370,
        author = {TANUSHREE CHANDEKAR and PROF. KALPESH KANPHADE and YASH WASANKAR and HITESH CHOUREWAR and KHUSHBU BHAISARE},
        title = {Analyzing The BLDC Motor For Automatic Gate},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {5},
        pages = {1055-1064},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=185370},
        abstract = {This paper presents a comprehensive analysis of brushless DC (BLDC) motor performance characteristics specifically tailored for automatic gate applications. Through systematic investigation of motor parameters, control strategies, and operational behaviors, this research provides detailed insights into BLDC motor optimization for gate automation systems. The analysis encompasses electromagnetic design principles, thermal characteristics, efficiency mapping, control algorithm performance, and system integration aspects. Experimental analysis conducted on multiple BLDC motor configurations reveals optimal design parameters achieving 89.2% peak efficiency, 0.95Nm/A torque density, and exceptional speed regulation of ±0.8% under varying load conditions. The study evaluates three distinct BLDC motor topologies: surface-mounted permanent magnet (SPM), interior permanent magnet (IPM), and hybrid permanent magnet configurations. Performance analysis demonstrates that IPM topology offers superior constant power speed range and 12% higher torque density, making it optimal for variable-load gate applications. Comprehensive thermal analysis shows that proper heat management enables 40% higher continuous power rating while maintaining temperature limits below 80°C. The research establishes design optimization guidelines, control parameter tuning methodologies, and performance prediction models specifically for gate automation applications. Economic analysis reveals that optimized BLDC motor designs can reduce system costs by 18% while improving performance metrics by 25-35% compared to conventional approaches.},
        keywords = {BLDC motor analysis, automatic gate, motor optimization, performance evaluation, electromagnetic design, thermal analysis, efficiency mapping},
        month = {October},
        }