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MathWorks Inc sim power systems
Sim Power Systems, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 94/100, based on 119 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/matlab+simulink+control+program/Simscape+Electrical/pm41775783-233-12-10
Average 94 stars, based on 119 article reviews

sim power systems - by Bioz Stars, 2026-11

94/100 stars

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Article Title: Thermally robust maximum power point tracking of proton exchange membrane fuel cells using hybrid Moth flame–Mayfly optimization
Article Snippet: All simulations were done using MATLAB/Simulink R2022b with the Simscape Electrical toolbox.

Article Title: Fuzzy-logic-controlled DVR for enhancing the fault resilience of wind energy conversion systems.
Article Snippet: A full system model in time domain is developed by MATLAB/Simulink with Sim Power Systems (Simscape Electrical – Specialized Power Systems) library.

Article Title: Adaptive linear MPC for a PMSM-driven autonomous EV with a filtered third-order generalized integrator observer
Article Snippet: The data that support the findings of this study are available from MathWorks Simscape Electrical (leveraged via King Fahd University of Petroleum and Minerals academic license) but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available.

Sampling:

Article Title: Low-Power Embedded Sensor Node for Real-Time Environmental Monitoring with On-Board Machine-Learning Inference.
Article Snippet: .. Given that no physical prototype is yet implemented, a detailed simulation framework has been developed in MATLAB R2023b (MathWorks, Natick, MA, USA), Simulink R2023b + Simscape Electrical R2023b to estimate subsystem power profiles, communication latency, and inference timing: • Sensor sampling and ADC models reflect datasheet-specified current draws; • MCU/NPU activity is modelled using cycle-accurate estimates from ARM CMSIS Power Estimator; • LoRaWAN stack simulation incorporates stochastic channel models for packet loss and ADR adaptation; • Battery and solar input are simulated using variable irradiance profiles (data from MeteoBlue for the UTAD region). .. MATLAB Simulink was selected as the primary modelling environment due to its native integration with Simscape Electrical and ARM CMSIS libraries, which allow cycleaccurate estimation of MCU/NPU activity and detailed component-level energy profiling.

Article Title: Low-Power Embedded Sensor Node for Real-Time Environmental Monitoring with On-Board Machine-Learning Inference
Article Snippet: .. Given that no physical prototype is yet implemented, a detailed simulation framework has been developed in MATLAB R2023b (MathWorks, Natick, MA, USA), Simulink R2023b + Simscape Electrical R2023b to estimate subsystem power profiles, communication latency, and inference timing: Sensor sampling and ADC models reflect datasheet-specified current draws; MCU/NPU activity is modelled using cycle-accurate estimates from ARM CMSIS Power Estimator; LoRaWAN stack simulation incorporates stochastic channel models for packet loss and ADR adaptation; Battery and solar input are simulated using variable irradiance profiles (data from MeteoBlue for the UTAD region). .. MATLAB Simulink was selected as the primary modelling environment due to its native integration with Simscape Electrical and ARM CMSIS libraries, which allow cycle-accurate estimation of MCU/NPU activity and detailed component-level energy profiling.

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Article Title: Hybrid hydrogen systems for mitigating sub synchronous oscillations in weak power grids
Article Snippet: Weak AC grids with high inverter-based renewable penetration are prone to sub-synchronous oscillations (SSOs), especially under low short-circuit ratio (SCR) conditions.. This paper proposes a hybrid energy storage system (HESS) combining fast-response electric double-layer capacitors (EDLCs) with slower hydrogen storage to enhance damping across multiple frequency ranges.. The methodology integrates detailed dynamic modeling of PEM electrolyzer and fuel-cell behavior, inverter–grid interactions, and a coordinated fast–slow control strategy that allocates rapid transient support to the EDLC and long-term balancing to the hydrogen subsystem.

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