Fuzzy-adaptive MPPT and Kalman-filter SOC estimation for Lyapunov-stable predictive energy management in solar-integrated EV charging stations

By Santhoshkumar, Suresh, Peramanan +1Scientific ReportsOct 18, 2026

Score████░░░░░░4.4

Key numbers

0.1% tracking efficiency over 15
0.6% for fixed-step P
0.2% for a linear-adaptive law

VerdictWorth a reader's time today.

Read the original

Abstract

This research develops a coordinated control, estimation, and dispatch framework for a solar-photovoltaic-integrated electric-vehicle charging station (EVCS) with battery storage and grid backup, and reports four contributions. First, a fuzzy-adaptive-step perturb-and-observe (P&O) maximum-power-point-tracking (MPPT) algorithm varies its perturbation step with the local power–voltage sensitivity and reaches 98.1% ± 0.1% tracking efficiency over 15 randomised irradiance scenarios with a single fixed parameter set, compared with 95.0% ± 0.6% for fixed-step P&O and 97.8% ± 0.2% for a linear-adaptive law re-tuned for each scenario (Welch’s t-test, t = 5.2, p < 0.0001, fuzzy-adaptive vs. re-tuned). Second, an extended Kalman filter (EKF) fuses Coulomb counting with a second-order Thevenin battery model to estimate state of charge (SOC), the pair is shown observable by a Popov–Belevitch–Hautus (PBH) test and, across 20 Monte Carlo trials, reduces mean SOC estimation RMSE from 2.45% to 0.118%. Third, a model-predictive-control (MPC) energy-management system (EMS) replaces static rule-based dispatch with receding-horizon optimisation, lowering operating cost by 6.8% under a perfect-forecast assumption while revealing an explicit trade-off against grid independence. Fourth, a switched-system stability analysis constructs mode-dependent Lyapunov functions and derives an average-dwell-time bound (τ_a* = 2.31 ms) that certifies exponential stability of the linearised converter dynamics for any mode-switching sequence respecting this bound. The complete simulation delivers 93.6% system efficiency, DC-bus regulation within ± 5%, and grid dependency of 14.2%. Of the four contributions, only the fuzzy-adaptive MPPT and EKF-SOC layers were implemented on an ESP8266 hardware prototype, on that subset, hardware-measured system efficiency (91.2%) agrees with simulation (93.6%) to within 2.4 percentage points. The MPC-EMS dispatch result and the Lyapunov stability proof remain simulation-level findings, and hardware validation of both is set out as a priority for future work.

R. Santhoshkumar, S. Suresh, A. Peramanan, P Sathish Kumar

The editor's rubric

Heuristic review

Leverage2 / 5: Reusable within one subfield (a technique, dataset, or protocol a few groups will adopt).; 16% of this desk’s rubric
Magnitude3 / 5: Large gain: roughly 2x, or a clear new state of the art on a hard, unsaturated problem.; 20% of this desk’s rubric
Evidence4 / 5: Strong: large scale, preregistered, independently replicated, or a well-powered randomized trial.; 20% of this desk’s rubric
Novelty2 / 5: A new combination of known ideas.; 10% of this desk’s rubric
Trajectory2 / 5: Some room to improve with obvious engineering.; 14% of this desk’s rubric
Stakes3 / 5: Meaningful benefit to many people within a few years.; 20% of this desk’s rubric

Dimension	Level	Weight	What that level means
Leverage	██░░░ 2	16%	Reusable within one subfield (a technique, dataset, or protocol a few groups will adopt).
Magnitude	███░░ 3	20%	Large gain: roughly 2x, or a clear new state of the art on a hard, unsaturated problem.
Evidence	████░ 4	20%	Strong: large scale, preregistered, independently replicated, or a well-powered randomized trial.
Novelty	██░░░ 2	10%	A new combination of known ideas.
Trajectory	██░░░ 2	14%	Some room to improve with obvious engineering.
Stakes	███░░ 3	20%	Meaningful benefit to many people within a few years.

Editor’s rationale

Heuristic triage from title and abstract text only, not a reading of the paper. Cues found: gains (relative gain); design (randomized); verification (p-value, error bars); scale (efficient); stakes (energy, climate).

How the score was computed

rank-2026-10-18

Score████░░░░░░4.4

Score = 10 × (75% × adjusted merit / 10 + 15% × attention + 10% × freshness)

Desks place stronger verdicts first, then use this score to order work within the same verdict.

Merit: 5.6 / 10; Weighted rubric, evidence-gated.
Adjusted merit: 4.7 / 10; Shrunk toward the desk prior by editor confidence (44%).
Attention: 0%; Citations, upvotes, points, mentions.
Freshness: 85%; Half-life decay since publication.

Citations0 (reference 15, via openalex, Oct 20, 2026, 07:29 UTC)

The record

Reviewed by heuristic-v7 on Oct 20, 2026, 07:29 UTC. Paper type: clinical.
Categories: Photovoltaic System Optimization Techniques, Electric Vehicles and Infrastructure, Power Systems and Renewable Energy, Renewable Energy, Sustainability and the Environment, Energy
TOP, No.4 in the Climate & Energy edition of October 20, 2026.