Manifold Absolute Pressure Sensor Research Articles

Monitoring of hydrogen-fueled engine backfires using dual manifold absolute pressure sensors

The application of hydrogen in internal combustion engines (ICE) has attracted widespread attention. However, due to the low ignition energy, high flame propagation speed, and wide combustible range of hydrogen, it is easy to cause abnormal combustion phenomena such as backfire in the port fuel injected (PFI) hydrogen-fueled engine. When a backfire occurs, the combustible mixture burns in the intake, resulting in a decrease in the volumetric efficiency of the engine, which may cause it to misfire or shut down in severe cases. Fast and accurate detection of backfire events is essential to take targeted control measures. In this research, a backfire detection system based on dual intake manifold absolute pressure (MAP) sensors were designed, with two MAP sensors installed on the intake manifolds of the first and fourth cylinders, and four gas injectors were installed on the intake manifold to convert the gasoline ICE into a hydrogen-fueled ICE. During the experiment, the engine speed was stabilized at 1000 rpm, the throttle valve was fully opened, and the intake pressure was maintained at 100 kPa.The test results show that the system can accurately determine the location and intensity of backfire occurrence. This method provides a basis for precise control of backfiring. • Set up two MAP sensors to monitor the backfiring of the hydrogen ICE. • MAP sensors allow accurate monitoring of backfiring. • Need to optimize valve strategy and injection strategy for hydrogen ICE.

EVALUATION METHODS AND WAYS OF IMPROVING THE OPERATIONAL DEPENDABILITY OF MASS AIRFLOW SENSORS IN ENGINES

The design of today’s car engine electronic control system practically always includes an engine load sensor. Normally, its role is played by the intake manifold absolute pressure sensor or the mass airflow sensor. Film mass airflow sensors are the most common ones. The sensor is installed in the intake between the air filter and the throttle plate of the engine intake manifold. In the process of operation the sensor is exposed to pollution and ageing of the gauging element due to interaction with dust particles and motor oil fumes in the airflow. That causes the output signal to deviate from the reference values and consequently inaccurate calculation of the fuel blend composition by the electronic engine control system. Given the design of the sensors, they cannot be repaired and are replaced with new ones. A new sensor is quite costly. Given the above, it is obvious that the subject is of relevance. The aim of the paper is to find methods of evaluation and ways of improving the operational dependability of film mass airflow sensors installed in modern automobiles. The evaluation of sensor operability is based on the voltage of the sensor output signal. Using a diagnostic scanner plugged into the automobile’s diagnostics port in the analog-to-digital converter channel viewing mode the voltage of the sensor output signal is recorded, the fuel blend long-lasting correction factor is evaluated, and the presence of error codes associated with the malfunction of mass airflow sensor in the memory of electronic control unit is verified. A digital oscilloscope is used for measuring the voltage at the moment of ignition lock activation and the resting voltage at zero airflow, as well as the transient time. Based on the obtained findings it becomes obvious that the operational dependability of such sensors can only be improved by correcting the calibration tables of the mass airflow sensor stored in the memory of the engine control unit. Using a mass airflow sensor test stand, input data is prepared for the correction procedure. The reference and tested sensors are installed on the same vacuum pump nozzle, and the airflow rate is changed gradually. Under a fixed airflow rate the sensors’ output voltage is measured. The resulting data is summarized in a table and processed with the Chip Tuning PRO calibration software. As can be seen, one of the causes of the loss of the sensors’ operational dependability is the pollution of the sensing element. The layer of pollution on the sensing element reduces the coefficient of heat transmission between the airflow and the sensor’s gauging element. Based on the conducted research, the paper presents the results of changing sensor output signal in operation as compared to the reference values, suggests a method of correction of the calibration table of mass airflow sensor parameters in the engine control program stored in the memory of the electronic control unit, provides recommendations regarding the methods of evaluation and ways of improving the sensors’ operational dependability.

Observer-Based Cylinder Air Charge Estimation for Spark-Ignition Engines

Spark-ignition engine in-cylinder air charge estimation is important for air-to-fuel ratio (AFR) control, maintaining high after-treatment efficiency, and determination of current engine torque. Current cylinder air charge estimation methodologies generally depend upon either a mass air flow (MAF) sensor or a manifold absolute pressure (MAP) sensor individually. Methods based on either sensor have their own advantages and disadvantages. Some production vehicles are equipped with both MAF and MAP sensors to offer air charge estimation and other benefits. This research proposes several observer-based cylinder air charge estimation methods that take advantage of both MAF and MAP sensors to potentially reduce calibration work while providing acceptable transient and steady-state accuracy with low computational load. This research also compares several common air estimation methods with the proposed observer-based algorithms using steady-state and transient dynamometer tests and a rapid-prototype engine controller. With appropriate tuning, the proposed observer-based methods are able to estimate cylinder air charge mass under different engine operating conditions based on the manifold model and available sensors. Methods are validated and compared based on a continuous tip-in tip-out operating condition.

Fault diagnosis for manifold absolute pressure sensor(MAP) of diesel engine based on Elman neural network observer

Intake system of diesel engine is a strong nonlinear system, and it is difficult to establish accurate model of intake system; and bias fault and precision degradation fault of MAP of diesel engine can’t be diagnosed easily using model-based methods. Thus, a fault diagnosis method based on Elman neural network observer is proposed. By comparing simulation results of intake pressure based on BP network and Elman neural network, lower sampling error magnitude is gained using Elman neural network, and the error is less volatile. Forecast accuracy is between 0.015-0.017 5 and sample error is controlled within 0-0.07. Considering the output stability and complexity of solving comprehensively, Elman neural network with a single hidden layer and with 44 nodes is presented as intake system observer. By comparing the relations of confidence intervals of the residual value between the measured and predicted values, error variance and failures in various fault types. Then four typical MAP faults of diesel engine can be diagnosed: complete failure fault, bias fault, precision degradation fault and drift fault. The simulation results show: intake pressure is observable and selection of diagnostic strategy parameter reasonably can increase the accuracy of diagnosis; the proposed fault diagnosis method only depends on data and structural parameters of observer, not depends on the nonlinear model of air intake system. A fault diagnosis method is proposed not depending system model to observe intake pressure, and bias fault and precision degradation fault of MAP of diesel engine can be diagnosed based on residuals.

Product Attribute Function Deployment (PAFD) for Decision-Based Conceptual Design

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> The critical product planning phase, early in the product development cycle, requires a design tool to establish engineering priorities, select the preferred design concept, and set target levels of engineering performance while considering the needs of both the consumer and producer. The quality function deployment (QFD) method was developed as a design process tool to translate customer needs into engineering characteristics; however, limitations have been identified in using the QFD method for product planning. In this paper, a new design tool called product attribute function deployment (PAFD), based on the principles of decision-based design (DBD), is introduced as a decision-theoretic, enterprise-level process tool to guide the conceptual design phase. The PAFD method extends the qualitative matrix principles of QFD while utilizing the quantitative decision-making processes of DBD. The PAFD method is built upon established methods in engineering, marketing, and decision analysis to eliminate the need for the user ratings and rankings of performance, priority, and attribute coupling in the QFD method. The differences between the QFD and the PAFD processes are compared and contrasted, and the conceptual design of an automotive manifold absolute pressure sensor is used as a case study to demonstrate the features and benefits of the PAFD method. </para>

Product Attribute Function Deployment for Decision-Based Conceptual Design

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> The critical product planning phase, early in the product development cycle, requires a design tool to establish engineering priorities, select the preferred design concept, and set target levels of engineering performance while considering the needs of both the consumer and producer. The quality function deployment (QFD) method was developed as a design process tool to translate customer needs into engineering characteristics; however, limitations have been identified in using the QFD method for product planning. In this paper, a new design tool called product attribute function deployment (PAFD), based on the principles of decision-based design (DBD), is introduced as a decision-theoretic, enterprise-level process tool to guide the conceptual design phase. The PAFD method extends the qualitative matrix principles of QFD while utilizing the quantitative decision-making processes of DBD. The PAFD method is built upon established methods in engineering, marketing, and decision analysis to eliminate the need for the user ratings and rankings of performance, priority, and attribute coupling in the QFD method. The differences between the QFD and the PAFD processes are compared and contrasted, and the conceptual design of an automotive manifold absolute pressure sensor is used as a case study to demonstrate the features and benefits of the PAFD method. </para>

Digital self-learning calibration system for smart sensors

Design and realization of a digitally controlled closed loop calibration system for smart sensors, capable of self-learning, is reported. Closed loop design enables analysis of sensor properties and optimization of calibration procedure. Dedicated software was developed, enabling control of acquired data and calibration procedure. Resulting statistical data provide closed loop feedback variable for failure analysis. Calibration system enables digital temperature compensation by acquisition of calibration points, calculation of sensor polynomial coefficients and storing the calculated data in the sensor memory. Due to the proposed digital temperature compensation method, temperature output error of pressure sensors was significantly reduced (typically from 0.15% FSO/°C to 0.05% FSO/°C, based on calibration of 29482 manifold absolute pressure sensors). Modular approach results in reduction of calibration time (typically down to 42 s/sensor), thus enabling mass calibration.

Sensitivity of hot film flow meter in four stroke gasoline engine

The air fuel ratios of current gasoline engines are almost controlled by several air flow meters. When CVVT (Continuous Variable Valve Timing) is applied to a gasoline engine for higher engine performance, the MAP (Manifold Absolute Pressure) sensor is difficult to follow the instantaneous air fuel ratio due to the valve timing effect. Therefore, a HFM (Hot Film Flow Meter) is widely used for measuring intake air flow in this case. However, the HFMs are incapable of indicating to reverse flow, the oscillation of intake air flow has an negative effect on the precision of the HFM. Consequently, the various duct configurations in front of the air flow sensor affect the precision of HFM sensitivity. This paper mainly focused on the analysis of the reverse flow, flow fluctuation in throttle upstream and the geometry of intake system which influence the HFM measurement.

MEMS' Rocky Road

This article highlights that there is potential demand for microelectromechanical systems (MEMS) devices across a range of industries. In 2002, the five leading applications of MEMS will use 21.5 million disposable blood pressure sensors, 28.7 million manifold absolute pressure sensors for engines, 85 million packaged airbag accelerometers, 425 million inkjet printer heads, and a whopping 1.58 billion read/write magnetic heads for computer hard drives. In MEMS, process is driven by design, so it is important for companies seeking to commercialize a micro device to evaluate the capabilities of a foundry. Industry groups are starting to recognize standardization as an issue, and are focusing on fabrication. The MEMS Industry Group, a trade association based in Pittsburgh, identified standardization as a key challenge in its 2001 annual report. The Group plans to issue a report on foundries and fabrication sooner.

A vertically integrated media-isolated absolute pressure sensor

A novel, media-isolated, temperature-compensated, bulk-micromachined integrated absolute pressure sensor has successfully been developed. The sensor is usable for most applications involving exposure to harsh media, such as fuel vapor seen by manifold absolute pressure (MAP) sensors. The device consists of two dice bonded together. Devices are batch fabricated by bonding two wafers together prior to sawing. The bottom wafer contains bulk-micromachined piezoresistive pressure sensors and the top wafer contains signal-conditioning integrated circuitry. The pressure sensors and the integrated circuits are coupled together by wirebonding from the top die down to the bottom die through via holes anisotropically etched in the top wafer. Characterization of the device indicates that the devices fabricated meet the specifications of a MAP sensor.

Failure mode testing tool set for automotive electronic controllers

The increasing complexity of automotive controllers requires the development and application of advanced tools to meet the challenges of software and systems integration testing. In the paper, a real-time hardware-in-the-loop simulation facility is presented for software verification. A dynamic laboratory environment, similar to the actual vehicle, facilitates the investigation and documentation of controller performance for prescribed operating scenarios. To support the verification of diagnostic software, a modular failure mode interface has been developed. A set of six failure modes is defined to automate the introduction of degradations into the controller's environment. The computer-controlled scheduler utility enables test sequences to be scheduled in a precise manner, while the data acquisition strategy logs time-synchronized data to verify the controller's operation. Three simulation test methods are presented for software verification. To demonstrate the capabilities and potential applications of this tool set, a series of manifold absolute pressure sensor failures is discussed.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>