High-Accuracy Low-Cost Cylinder Pressure Sensor for Advanced Engine Controls

Author(s):  
Otho Ulrich ◽  
Rapheal Wlodarczyk ◽  
Marek T. Wlodarczyk
Sensors ◽  
2019 ◽  
Vol 19 (14) ◽  
pp. 3122
Author(s):  
Qiming Wang ◽  
Tao Sun ◽  
Zhichao Lyu ◽  
Dawei Gao

As a crucial and critical factor in monitoring the internal state of an engine, cylinder pressure is mainly used to monitor the burning efficiency, to detect engine faults, and to compute engine dynamics. Although the intrusive type cylinder pressure sensor has been greatly improved, it has been criticized by researchers for high cost, low reliability and short life due to severe working environments. Therefore, aimed at low-cost, real-time, non-invasive, and high-accuracy, this paper presents the cylinder pressure identification method also called a virtual cylinder pressure sensor, involving Frequency-Amplitude Modulated Fourier Series (FAMFS) and Extended-Kalman-Filter-optimized (EKF) engine model. This paper establishes an iterative speed model based on burning theory and Law of energy Conservation. Efficiency coefficient is used to represent operating state of engine from fuel to motion. The iterative speed model associated with the throttle opening value and the crankshaft load. The EKF is used to estimate the optimal output of this iteration model. The optimal output of the speed iteration model is utilized to separately compute the frequency and amplitude of the cylinder pressure cycle-to-cycle. A standard engine’s working cycle, identified by the 24th order Fourier series, is determined. Using frequency and amplitude obtained from the iteration model to modulate the Fourier series yields a complete pressure model. A commercial engine (EA211) provided by the China FAW Group corporate R&D center is used to verify the method. Test results show that this novel method possesses high accuracy and real-time capability, with an error percentage for speed below 9.6% and the cumulative error percentage of cylinder pressure less than 1.8% when A/F Ratio coefficient is setup at 0.85. Error percentage for speed below 1.7% and the cumulative error percentage of cylinder pressure no more than 1.4% when A/F Ratio coefficient is setup at 0.95. Thus, the novel method’s accuracy and feasibility are verified.


2020 ◽  
Author(s):  
Derek Schulte ◽  
Kyam Krieger ◽  
Carl W. Chin ◽  
Alexander Sonn
Keyword(s):  
Low Cost ◽  

Author(s):  
Jonas Austerjost ◽  
Robert Söldner ◽  
Christoffer Edlund ◽  
Johan Trygg ◽  
David Pollard ◽  
...  

Machine vision is a powerful technology that has become increasingly popular and accurate during the last decade due to rapid advances in the field of machine learning. The majority of machine vision applications are currently found in consumer electronics, automotive applications, and quality control, yet the potential for bioprocessing applications is tremendous. For instance, detecting and controlling foam emergence is important for all upstream bioprocesses, but the lack of robust foam sensing often leads to batch failures from foam-outs or overaddition of antifoam agents. Here, we report a new low-cost, flexible, and reliable foam sensor concept for bioreactor applications. The concept applies convolutional neural networks (CNNs), a state-of-the-art machine learning system for image processing. The implemented method shows high accuracy for both binary foam detection (foam/no foam) and fine-grained classification of foam levels.


2013 ◽  
Author(s):  
Erica Nocerino ◽  
Fabio Menna ◽  
Salvatore Troisi
Keyword(s):  
Low Cost ◽  

2013 ◽  
Vol 834-836 ◽  
pp. 930-934
Author(s):  
Shou Liang Yang ◽  
Bao Liang Yang

The paper proposes a new design of high-accuracy On-line Metal Thickness Measuring Instrument, which was based on EP2C20 series FPGA chip, through adding NiosII soft processor and other interfaces to FPGA, equipped with high precision data collection system and TFT LCD module and so on. The key hardware blocks schematics and components of the RC Oscillation Circuit,eddy current sensor Circuit,rectifier and filter Circuit,A/D converting circuit,FPGA Circuit are described,software flow charts and sample codes are given. According to practice, The measurement range of this system is 1~100 mm and the resolving power is 0.1 μm. degree of linearity is 1%, The system has many features including small volume of hardware, low cost, high detecting precision, convenient operating, high intelligent and so on, leading to broad and bright future. Key words: NiosII processor; eddy current sensor; metal thickness


Sensors ◽  
2018 ◽  
Vol 18 (7) ◽  
pp. 2382 ◽  
Author(s):  
Antonio Vidal-Pardo ◽  
Santiago Pindado

In this work, a new and low-cost Arduino-Based Data Acquisition System (ABDAS) for use in an aerodynamics lab is developed. Its design is simple and reliable. The accuracy of the system has been checked by being directly compared with a commercial and high accuracy level hardware from National Instruments. Furthermore, ABDAS has been compared to the accredited calibration system in the IDR/UPM Institute, its measurements during this testing campaign being used to analyzed two different cup anemometer frequency determination procedures: counting pulses and the Fourier transform. The results indicate a more accurate transfer function of the cup anemometers when counting pulses procedure is used.


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