The convergence of smart sensing, renewable energyconversion, and advanced battery management is reshapingthe landscape of modern electrical infrastructure. This paperpresents a unified benchmarking study spanning five tightly cou-pled technical domains: (i) smart contactless height measurementusing an Arduino-based ultrasonic sensing platform with mobileapplication integration; (ii) next-generation solar grid integrationusing a 400 kW Modular Multilevel Converter (MMC) coupledwith Maximum Power Point Tracking (MPPT) control; (iii) opti-mization of residential grid-connected photovoltaic (PV) systemsunder partial shading using fuzzy logic-based MPPT; (iv) logicalnumerical modeling of Battery Energy Storage Systems (BESS)for peak shaving, load shifting, and load leveling in smart gridscenarios; and (v) advanced nonlinear State-of-Charge (SOC) andcapacity estimation for degrading battery systems via UnscentedKalman Filtering (UKF). Collectively, these five contributionsform a coherent pipeline from physical measurement at thegrid edge through large-scale renewable energy conversion toprecise battery lifecycle management. Key findings confirm thatthe ultrasonic smart scale achieves sub-1% relative measurementerror across a range of 2 cm to 13 feet; the MMC-MPPTarchitecture achieves a Total Harmonic Distortion (THD) be-low 5% with output voltage stabilization within 0.8 seconds;the fuzzy logic MPPT recovers 48.3% additional power underpartial shading compared to local-maximum tracking; the BESSnumerical model successfully simulates grid-service scenarios inMATLAB/Simulink; and the UKF achieves SOC estimation ac-curacy within 0.6% of actual values, outperforming conventionalKalman filter approaches by approximately 10% in capacityestimation accuracy. These results collectively demonstrate thepotential of integrated hardware–software co-design for next-generation smart energy infrastructure.
Arman Mithila (2026) studied this question.