Smart BMS & Battery Analytics
ECM 3RC, UKF, LSTM residual correction, SOC/SOH estimation.
Open to engineering opportunities
Three values guide my work: integrity, quality and curiosity.
My work connects BMS design, embedded systems, battery analytics, and production supervision into practical engineering solutions.
ECM 3RC, UKF, LSTM residual correction, SOC/SOH estimation.
STM32, Altium Designer, 16S BMS, EMC, protections, CAN/I2C/SPI.
MQTT, REST API, dashboards, KPI monitoring, production traceability.
State Engineer in Electrical Engineering and Industrial Systems Control, with a research focus on smart Battery Management Systems, battery analytics, and AI-assisted SOC estimation for LiFePO4 batteries. Experienced in physical battery modeling, ECM-based simulation, Unscented Kalman Filtering, LSTM residual correction, and digital-twin-based validation for electric mobility applications. Skilled in MATLAB/Simulink, Python, embedded systems, and industrial data acquisition, with strong interest in predictive modeling, SOH estimation, anomaly detection, and real-time battery health monitoring.
Feb 2026 – May 2026
Project: Systemic resolution of a critical premature shutdown defect (at 20% SoC) and energy gauge instability during abrupt accelerations on electric scooters through a coupled Hardware / Software / Process approach.
July 2025 – September 2025
Industrial Automation (PLC/HMI), Mechanical Design
Software Used: TIA Portal, Autodesk Inventor
July 2024 – August 2024
National Office of Electricity and Water
Software Used: OMICRON Test Universe, SIPROTEC Tools
2020 – 2023 (3 Years)
Mechanical Repair, CNC & Robotics
2023 - 2026
ENSET Mohammedia
Electrical Engineering and Industrial Systems Control
2022 - 2023
Faculty of Sciences Ben M'sik, Casablanca
Electronics Specialization
2020 - 2022
Faculty of Sciences Ben M'sik, Casablanca
General Physics and Chemistry
2019 - 2020
Technical High School, Mohammedia
Electrical Specialization
End-of-studies internship project focused on LFP scooter battery reliability, combining ECM/UKF/LSTM SOC estimation, STM32-based BMS hardware architecture, battery quality procedures, and industrial supervision.
Designed and simulated advanced 3D microwave channels using ANSYS HFSS. By precisely visualizing the complex electric and magnetic fields, I proved how integrating a ceramic dielectric (Alumina) drastically shrinks the system's physical footprint
Conducted a comparative study of Lumped Capacitance Modeling vs. FEA (ANSYS, Fusion 360) to validate the cycle time for automated hot nut insertion in polycarbonate.
Designed a full autopilot system (Luenberger Observer + State-Feedback Controller) to achieve orbital rendezvous using only angle-data ($y=\theta$), overcoming numerical instability via system normalization.
LV Electrical System Design, Sizing & Code Compliance for a Pumping Station. (Software: Caneco BT, ETAP)
Systemic resolution of premature shutdown and energy gauge instability on electric scooters
Built a coupled Hardware / Software / Process approach around a high-fidelity Digital Twin, hybrid SoC estimation, active balancing, embedded BMS hardware, HiL validation, and production traceability.
State Engineer in Electrical Engineering and Industrial Systems Control, with a research focus on smart Battery Management Systems, battery analytics, and AI-assisted SOC estimation for LiFePO4 batteries. Experienced in physical battery modeling, ECM-based simulation, Unscented Kalman Filtering, LSTM residual correction, and digital-twin-based validation for electric mobility applications. Skilled in MATLAB/Simulink, Python, embedded systems, and industrial data acquisition, with strong interest in predictive modeling, SOH estimation, anomaly detection, and real-time battery health monitoring.