Öz
Kaynakça
- V. Ganesan, IC Engines, 4th ed, New Delhi: Tata McGraw Hill Education Private Limited, 2012.
- M. A. J. Matos, "ECG Denoising Based on Adaptive Signal Processing Technique," M.S. thesis, Instituto Superior de Engenharia do Porto, November. 2011. [Online]. Available: https://core.ac.uk/download/pdf/302861698.pdf. [Accessed January 2023].
- L. F. Eugênio, M. G. Lucas, O. d. A. L. F. José, C. d. C. Mário, G. S. L. c. Luis, L. d. L. Marcelo and S. T. Eduardo, "Model-free adaptive filter to mitigate actuator wear," ISA Transactions, vol. 129, pp. 493-504, 2022.
- G. Xin, J. Changwei, S. Wang, H. Meng, K. Chang, J. Yang and C. Hong, "Monitoring of hydrogen-fueled engine backfires using dual manifold absolute pressure sensors," International Journal of Hydrogen Energy, vol. 47, no. 26, pp. 13134-13142, 2022. "Estimate the Power Spectrum in MATLAB," MATLAB, [Online]. Available: https://www.mathworks.com/help/dsp/ug/estimate-the-power-spectrum-in-matlab.html. [Accessed January 2023].
- S. Haykin, Adaptive Filter Theory, 5th ed, NJ: Prentice Hall, 2014.
- P. S. R. Diniz, Adaptive Filtering Algorithms and Practical Implementation, 4th Ed., Rio de Janeiro: Springer, 2013.
- S. C. Douglas, "Introduction to Adaptive Filters," in Digital Signal Processing Handbook, CRC Press LLC, 1999.
- S. Dixit and D. Nagaria, "LMS Adaptive Filters for Noise Cancellation: A Review," International Journal of Electrical and Computer Engineering (IJECE), vol. 7, no. 5, pp. 2520-2529, 2017.
- T. Moon and T. Weissman, "Universal FIR MMSE Filtering," IEEE TRANSACTIONS ON SIGNAL PROCESSING, vol. 57, no. 3, pp. 1068-1083, 2009.
- S. Kim and H. Kim, "A new metric of absolute percentage error for intermittent demand forecasts," International Journal of Forecasting, no. 32, pp. 669-679, 2016.
Öz
This study proposes an adaptive filter based on a manifold absolute pressure (MAP) sensor in order to control automotive engines. The proposed adaptive filter, which is based on the least mean squares (LMS) algorithm, is intended to reduce the impacts of sensor noise and nonlinearity, which can result in false readings and a subsequent decline in engine performance. The filter can be used for long-term engine control applications because it is implemented on a model-based system and can adapt to changes in the sensor's properties over time. The suggested filter efficiently decreases sensor noise and increases the accuracy of MAP sensor readings, according to experimental data, which also indicate a roughly 10% rise in mean absolute percentage error (MAPE) compared to the standard lowpass filter. The filter's versatility also enables reliable operation under a variety of operating conditions and sensor characteristics. Additionally, the filter's signal-to-noise ratio (SNR) enhancement is almost 10% greater than that of a traditional lowpass filter, resulting in enhanced engine performance and fuel economy. Overall, the suggested adaptive filter appears to be a viable option for improving the performance of MAP sensors in automotive engine control applications.
Anahtar Kelimeler
Signal processing digital filtering adaptive filtering manifold absolute pressure
Kaynakça
- V. Ganesan, IC Engines, 4th ed, New Delhi: Tata McGraw Hill Education Private Limited, 2012.
- M. A. J. Matos, "ECG Denoising Based on Adaptive Signal Processing Technique," M.S. thesis, Instituto Superior de Engenharia do Porto, November. 2011. [Online]. Available: https://core.ac.uk/download/pdf/302861698.pdf. [Accessed January 2023].
- L. F. Eugênio, M. G. Lucas, O. d. A. L. F. José, C. d. C. Mário, G. S. L. c. Luis, L. d. L. Marcelo and S. T. Eduardo, "Model-free adaptive filter to mitigate actuator wear," ISA Transactions, vol. 129, pp. 493-504, 2022.
- G. Xin, J. Changwei, S. Wang, H. Meng, K. Chang, J. Yang and C. Hong, "Monitoring of hydrogen-fueled engine backfires using dual manifold absolute pressure sensors," International Journal of Hydrogen Energy, vol. 47, no. 26, pp. 13134-13142, 2022. "Estimate the Power Spectrum in MATLAB," MATLAB, [Online]. Available: https://www.mathworks.com/help/dsp/ug/estimate-the-power-spectrum-in-matlab.html. [Accessed January 2023].
- S. Haykin, Adaptive Filter Theory, 5th ed, NJ: Prentice Hall, 2014.
- P. S. R. Diniz, Adaptive Filtering Algorithms and Practical Implementation, 4th Ed., Rio de Janeiro: Springer, 2013.
- S. C. Douglas, "Introduction to Adaptive Filters," in Digital Signal Processing Handbook, CRC Press LLC, 1999.
- S. Dixit and D. Nagaria, "LMS Adaptive Filters for Noise Cancellation: A Review," International Journal of Electrical and Computer Engineering (IJECE), vol. 7, no. 5, pp. 2520-2529, 2017.
- T. Moon and T. Weissman, "Universal FIR MMSE Filtering," IEEE TRANSACTIONS ON SIGNAL PROCESSING, vol. 57, no. 3, pp. 1068-1083, 2009.
- S. Kim and H. Kim, "A new metric of absolute percentage error for intermittent demand forecasts," International Journal of Forecasting, no. 32, pp. 669-679, 2016.
Ayrıntılar
| Birincil Dil | İngilizce |
|---|---|
| Konular | Sorgu İşleme ve Optimizasyon, Veri Kalitesi, Veri Mühendisliği ve Veri Bilimi |
| Bölüm | Research Articles |
| Yazarlar | |
| Yayımlanma Tarihi | 15 Aralık 2023 |
| Gönderilme Tarihi | 19 Haziran 2023 |
| Yayımlandığı Sayı | Yıl 2023 Cilt: 3 Sayı: 2 |
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