## 2 Materials and Method  
### Materials  
The experimental system comprises commercial and custom-designed components to achieve non-invasive rotational speed detection. A 32-bit microcontroller (STM32F407 VGT6, STMicroelectronics; sourced from Shenzhen JLCPCB Technology Development Co., Ltd., Shenzhen, China) was employed as the main processing unit. This device features an ARM Cortex-M4 core operating at 168 MHz and integrates a 12-bit analog-to-digital converter (ADC) capable of signal acquisition at a sampling rate of 5 kHz. Signal conditioning is implemented through a custom-designed circuit (simulated in Altium Designer 2018), providing noise filtering and amplification to isolate alternator-induced AC components from the cigarette lighter signal. Power isolation is ensured via a two-stage regulation system: an LM2596-5V isolated DC-DC converter (Texas Instruments, Dallas, TX, USA) reduces the 12 V input from an external independent power source to 5 V, followed by an AMS1117-3.3V LDO regulator (Advanced Monolithic Systems) to ensure a precise 3.3 V supply to sensitive analog circuits.  
Embedded software, developed using Keil uVision5 (MDK v5.38), implements real-time signal processing algorithms, including FFT-based spectral analysis and phase compensation, through an optimized C code. A LabWindows/CVI 2023-based interactive display unit enables parameter tuning and visualization, interfacing with the microcontroller via UART. Critical component specifications are summarized in Table 1 for reproducibility.  
Table 1 details key component specifications and provides a comparative analysis with existing systems. The table compares the proposed system with conventional contact sensors, OBD-II-based tools, and vibration-based non-contact methods, including hardware architecture, software algorithms, signal conditioning, power supply design, and cost-effectiveness. Comparative metrics emphasize the non-intrusive plug-and-play operation  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Category** & **Proposed System** & **Conventional Contact-Type [13]** & **OBD-II Based Tools [32]** & **Vibration-Based Non-Contect [33]** \\ \hline \multirow{4}{*}{Main Processor} & STM32F40 VGT6 (ARM Cortex-M4, 168 MHz; sourced from Shenzhen JLCPCB Technology Development Co., Ltd., Shenzhen, China) & Dedicated sensor module (e.g., Hall-effect ICs, Allegro Systems, Worcester, MA, USA) & Commercial OBD scanner (e.g., ELM327, 3-bit MCU, Micro Technology Inc., Chandler, AZ, USA) & DSP processors (e.g., TI C2000, 120 MHz, Texas Instruments, Dallas, TX, USA) \\  & I2-bit ADC, 5 kHz sampling & 10-bit ADC, 500 Hz sampling & CAN bus decoding (250 kbps) & 16-bit ADC, 5 kHz sampling \\  & Custom circuit & J1979-compliant, ELM327 & IEP accelerometers(PCB \\ Conditioning & (Altium-designed 2018, 410 MF noise) & Passive RC filters & clupster, Texas Instruments, USA) signal passstrophy (no conditioning) & Piezoformics, Depew, NY, USA) + charge amplifiers \\  & Isolated LM2596-5V + & & Vehicle battery (12 V direct) & Vehicle battery (risk of ground loops) \\ Power Supply & AMS117-3.3V (decoupled from vehicle power) & & & \\  & Vendor-specific firmware v1.2.3 & Proprietary OBD app FLAG327 & MATLAB R2023 (MathWorks, Natick, MA, USA)/Python 3.9.7 \\ Software & Keil uVision5 (FFT + phase compensation in C) & (Custom OBD-II Protocol (closed-source.) & v2.4 (e.g., Torque Pro) & C-Python, Open-Source) \\  & LabWindows/CVI 2023 & Mechanical dial gauges & Smartphone/tablelet & PC-based DAQ systems (e.g., NI via Bluetooth \\  & (real-time visualization) & & & \\  & & & \\  & & & \\  & & & & \\  & & & \\  & & & \\ \end{tabular}
\end{table}
Table 1: Critical component specifications.  
of the proposed system, avoiding the mechanical coupling limitations of contact sensors [13] and the ambient noise sensitivity of vibration-based approaches [34], while reducing the hardware cost compared to commercial DAQ systems.