Universal Exhaust Gas Oxygen Sensor Research Articles

Study on backfire characteristics of port fuel injection single-cylinder hydrogen internal combustion engine

Hydrogen energy is one of the most promising sources of carbon neutrality from well to wheel. Among various applications of hydrogen energy, hydrogen internal combustion engines serve as the critical technical pathway. Nevertheless, several challenges persist, primarily related to abnormal combustion resulting from excessive flame propagation velocity. Of these challenges, backfire emerges as the most recurrent and pressing issue to be resolved in the port fuel-injected hydrogen internal combustion engine (PFI-H2ICE). In order to delve into the characteristics and mechanisms of backfire, this study concentrates on a critical internal parameter, namely the start of injection (SOI), and comprehensively assesses the backfire occurrences under varying lambda and engine speed conditions. Experimental findings reveal that SOI encompasses one of the pivotal factors influencing backfire. Backfire predominantly arises within two ranges of SOI conditions: the region before −430 degCA ATDC (Zone I) and the stretch between −360 degCA ATDC and − 280 degCA ATDC (Zone II). In the process of employing EGR to depress the effects of backfire on subsequent tests, it was incidentally found that the Universal Exhaust Gas Oxygen Sensor (UEGO) installed on the intake manifold for executing EGR rate calculations acted as a hotspot (with temperatures exceeding 100 °C). This not only intensified the backfire strength and the scope in Zone I but also caused the most severe backfire events to occur after −270 degCA ATDC (in Zone III). Despite this, the EGR strategy still demonstrated a significant backfire suppression effect, only exhibiting almost no influence on backfire caused by hotspots within the intake manifold. With an escalation in engine speed, the intensity of backfire diminishes, and the range of backfire occurrence decreases accordingly. By exercising control over SOI within the operating range from -430degCA to -360degCA ATDC (Zone A), the risk of backfire can be dramatically reduced, thereby achieving nearly backfire-free operation. Detailed analysis of cylinder pressure indicates that backfire may also give rise to other abnormal combustions, such as misfire, pre-ignition, and knock, in subsequent cycles. Moreover, this effect amplifies in tandem with an increase in mixture concentration. A certain degree of mutual promotion among diverse abnormal combustions is also observed. This study furnishes the most direct and practical foundation for internal and external strategies in the realm of backfire control.

An Air-to-Fuel ratio estimation strategy for turbocharged spark-ignition engines based on sparse binary HEGO sensor measures and hybrid linear observers

An effective Air-to-Fuel Ratio (AFR) control is paramount to ensure a good combustion and high catalyst efficiency. This work addresses the problem of determining continuous-time estimates of AFR in turbocharged Spark Ignition (SI) engines on the basis of binary sparse measurements of the exhaust gas Oxygen. The latter are provided by a HEGO (Heated Exhaust Gas Oxygen) sensor installed at the catalytic converter input in place of a more expensive linear UEGO (Universal Exhaust Gas Oxygen) sensor, as nowadays common in commercial cars. The HEGO sensor outputs two voltage values only, corresponding respectively to low or high concentration of the residual Oxygen in the exhaust gas (on/off behavior). In view of this, it can be classified as a binary sensor generating irregular and sparse measurements in that the useful information is only present at the instants of the on/off and off/on transitions. An estimation scheme based on the use of a recursive least-squares algorithm has been designed by resorting to the theory of linear hybrid observers with quantized inputs. A detailed convergence analysis of the state reconstruction error is also provided. The proposed hybrid observer scheme is employed in a PI control-loop designed to maintain the AFR close to a desired value. The effectiveness of the proposed method is demonstrated by several numerical simulations based on both synthetic and real data.

Excess Air Ratio Management in a Diesel Engine with Exhaust Backpressure Compensation.

The paper investigates the operation of a wideband universal exhaust gas oxygen (UEGO) sensor in a diesel engine under elevated exhaust backpressure. Although UEGO sensors provide the excess air ratio feedback signal primarily in spark ignition engines, they are also used in diesel engines to facilitate low-emission combustion. The excess air signal is used as an input for the fuel mass observer, as well as to run the engine in the low-emission regime and enable smokeless acceleration. To ensure a short response time and individual cylinder control, the UEGO sensor can be installed upstream of a turbocharger; however, this means that the exhaust gas pressure affects the measured oxygen concentration. Therefore, this study determines the sensor’s sensitivity to the exhaust pressure under typical conditions for lean burn low-emission diesel engines. Identification experiments are carried out on a supercharged single-cylinder diesel engine with an exhaust system mimicking the operation of the turbocharger. The apparent excess air measured with the UEGO sensor is compared to that obtained in a detailed exhaust gas analysis. The comparison of reference and apparent signals shows that the pressure compensation correlations used in gasoline engines do not provide the correct values for diesel engine conditions. Therefore, based on the data analysis, a new empirical formula is proposed, for which the suitability for lean burn diesel engines is verified.

Parameter Identification of Nonlinear System on Combustion Engine Based MVEM using PEM

In four-stroke engine injection system, often called spark ignition (SI) engine, the air-fuel ratio (AFR) is taken from the measurement of lambda sensor in the exhaust. This sensor does not directly describe how much AFR in the combustion chamber due to the large transport delay. Therefore, the lambda sensor is used only as a feedback in AFR control "correction", not as the "main" control. The purpose of this research is to identify the parameters of the non-linear system in SI engines to produce AFR estimator. The AFR estimator is expected to be used as a feedback of the main "AFR" control system. The process of identifying the parameters using the Gauss-Newton method, due to its rapid computation to Achieve convergence, is based on prediction error minimization (PEM). The models of AFR estimator is an open-loop system without a universal exhaust gas oxygen (UEGO) sensors as feedback, called a virtual AFR sensor. The high price of UEGO sensors makes the virtual AFR sensor can be a practical solution to be applied in AFR control. The model in this research is based on the mean value engine models (MVEM) with some modifications. The research dataset was taken from a Hyundai Verna 2002 with the additional UEGO type of lambda sensors. The throttle opening angle (input) is played by stepping on the gas pedal and the signal to the injector (input) is set to a certain quantity to produce the AFR (output) value read by the UEGO sensor. This research produces an open loop estimator model or AFR virtual sensors with normalized root mean square error (NRMSE) = 0.06831 = 6.831%.

The transient start-up response of a universal exhaust gas oxygen sensor to investigate the Nernst equation in platinum/zirconia cells

The universal exhaust gas oxygen sensor (UEGO) is a device used to infer the combustion air-to-fuel ratio of an internal combustion engine by sampling the exhaust gas. The sensor operates using a feedback system to maintain a specified internal condition, and measures the oxygen current required for this. While the steady state operation of the sensor is reasonably well-understood – dominated as it is by the diffusion of gas species – the factors influencing the transient response are not so clear.In this paper a numerical model of a sensor is compared to experimental data. By examining the effect of the inclusion of different aspects into the model, it becomes clear that it is necessary to account for the influence of gaseous species adsorbing onto surfaces, as well as the more traditional approach based on oxygen partial pressure, to correctly capture the transient response of a sensor containing a Pt|YSZ|Pt cell.

Robust Control of the Air to Fuel Ratio in Spark Ignition Engines with Delayed Measurements from a UEGO Sensor

A precise control of the normalized air to fuel ratio in spark ignition engines is an essential task. To achieve this goal, in this work we take into consideration the time delay measurement presented by the universal exhaust gas oxygen sensor along with uncertainties in the volumetric efficiency. For that purpose, observers are designed by means of a super-twisting sliding mode estimation scheme. Also two control schemes based on a general nonlinear model and a similar nonlinear affine representation for the dynamics of the normalized air to fuel ratio were designed in this work by using the super-twisting sliding mode methodology. Such dynamics depends on the control input, that is, the injected fuel mass flow, its time derivative, and its reciprocal. The two latter terms are estimated by means of a robust sliding mode differentiator. The observers and controllers are designed based on an isothermal mean value engine model. Numeric and hardware in the loop simulations were carried out with such model, where parameters were taken from a real engine. The obtained results show a good output tracking and rejection of disturbances when the engine is closed loop with proposed control methods.

Significance of gasification during oxy-fuel combustion of a lignite char in a fluidised bed using a fast UEGO sensor

In oxy-fuel combustion, fuel is combusted in a mixture of O2 and recycled flue gas, i.e. the N2 is replaced by CO2 with the O2 supplied from an air separation unit. The resulting gas consists largely of steam and CO2, which would be ready for sequestration when dried. In this work, the rate of reaction of particles of lignite char, typically 1200μm diameter, in a fluidised bed reactor was determined using mixtures of O2 with either CO2 (“oxy-fuel”) or N2. A universal exhaust-gas oxygen (UEGO) sensor enabled rapid measurements of the oxygen partial pressures in the off-gas, representing a novel application of this type of sensor. It was found that the rate of combustion of the particles in oxy-fuel is much more sensitive to temperature than in the equivalent O2 and N2 mixture. This is because for bed temperatures >∼1000K particle combustion in mixtures of N2 and O2 is rate controlled by external mass transfer, which does not increase significantly with temperature. In contrast, using oxy-fuel, as the temperature increases, gasification by the high concentrations of CO2 present becomes increasingly significant. At low temperatures, e.g. ∼1000K, rates of combustion in oxy-fuel were lower than those in mixtures of O2 and N2 containing the same mole fraction of O2 owing, primarily, to the lower diffusivities of O2 in CO2 compared to O2 in N2 under conditions at which external mass transfer is still a significant factor in controlling the rate of reaction. At higher temperatures, e.g. 1223K, oxy-fuel combustion rates were significantly higher than those in O2 and N2. The point at which oxy-fuel combustion becomes more rapid than in mixtures of O2 and N2 depends not only on temperature but also on the ratio of O2 to CO2 or N2, respectively. A numerical model was developed to account for external mass transfer, changes in the temperature of the particle and for the effect of gasification under oxy-fuel conditions. The model confirmed that, at high temperatures, the high concentration of CO2 at the surface of the burning particle in the oxy-fuel mixture led to an increase in the overall rate of carbon conversion via CO2+C→2CO, whilst the rate of reaction with O2 was limited by mass transfer. Good agreement was observed between the rates predicted by the numerical model and those observed experimentally.

Design of Heating Control System for UEGO Sensor

Universal Exhaust Gas Oxygen (UEGO) Sensor is one of the most important sensors for the close-loop air-fuel-ratio control system of automobile engine. Due to its special structure, controller is used to control sensors temperature so that UEGO sensor can work normally. Aiming at nonlinear characteristic of the temperature control module, a subsection heating control method and a PID algorithm is studied. UEGO heating controller is implemented by means of Motohawk real time simulation system. Experimental results show that under the condition of different temperature, the UEGO is also able to maintain the best working temperature.

Estimating IC engine exhaust gas lambda and oxygen from the response of a universal exhaust gas oxygen sensor

Universal exhaust gas oxygen sensors (UEGOs) are in widespread use in internal combustion engines where they are used to measure lambda (the non-dimensional air–fuel ratio) and oxygen concentration (). The sensors are used on production engines and for research and development. In a previous paper, a model of the UEGO sensor was presented, based on a solution of the Stefan–Maxwell equations for an axisymmetric geometry, and it was shown that for a known gas composition, predictions of the sensor response agreed well with experiment. In the present paper, the more ‘practical’ problem is addressed: how well can such a model predict λ and based on the sensor response? For IC engine applications, a chemistry model is required in order to predict λ, and such a model is also desirable for an accurate prediction of . A fast (matrix exponential) method of solving the Stefan–Maxwell equations is also introduced, which offers the possibility of a near real-time computation of λ and , with application, for example, to bench instruments. Extensive results are presented showing how the interpretation of the UEGO response may be compromised by uncertainties. These uncertainties may relate not only to the sensor itself, such as temperature, pressure and mean pore diameter, but also the chemistry model.

A new method for measurement of air–fuel ratio based on the response time of binary-type exhaust gas oxygen (BEGO) sensor for application in small spark ignition (SI) engines

A binary-type exhaust gas oxygen (BEGO) sensor that is usually used to maintain the air–fuel ratio (AFR) at stoichiometric conditions in current spark ignition (SI) engines is significantly lower in cost compared with the universal exhaust gas oxygen sensor. However, it can only switch from a high state (≈0.7 V) to a low state (≈0.1 V) when the mixture goes from richer to leaner than stoichiometric conditions or vice versa. Thus, it cannot indicate the actual AFR. A novel method of estimating the AFR of an SI engine using a BEGO sensor has been demonstrated in this work for leaner than stoichiometric mixtures. Experiments were conducted on a single-cylinder, manifold-injection SI engine. The air–fuel mixture was initially kept at a richer than stoichiometric level while the engine was maintained at constant speed and throttle. The mixture was suddenly changed to a leaner than stoichiometric level. The switching time of the BEGO sensor during this operation was noted. This was repeated for different initial and final AFRs. A relationship between the switching time and change in AFR was obtained for different initial AFRs. A look-up table to determine the AFR was made and used under test conditions. The error is less than 5% in the estimated AFR. The system was also incorporated on a low-cost microcontroller-based engine management system and tested under laboratory conditions.

A parameter-varying filtered PID strategy for air–fuel ratio control of spark ignition engines

In this paper, a new synthesis method is presented to control air–fuel ratio (AFR) in spark ignition engines to maximize the fuel economy while minimizing exhaust emissions. The major challenge in the control of AFR is the time-varying delay in the control loop which restricts the application of conventional control techniques. In this paper, the time-varying delay in the system dynamics is first approximated by Padé approximation to render the system dynamics into non-minimum phase characteristics with time-varying parameters. Application of parameter-varying dynamic compensators is invoked to retrieve unstable internal dynamics. The associated error dynamics is then utilized to construct a filtered PID controller combined with a parameter-varying dynamic compensator to track the desired AFR command using the feedback from the universal exhaust gas oxygen sensor. The proposed method achieves desired dynamic properties independent of the matched disturbances. It also accommodates the unmatched perturbations due to the dynamic compensator features. The results of applying the proposed method to experimental numerical data demonstrate the closed-loop system stability and performance against time-varying delay, canister purge disturbances and measurement noise for both port fuel injection engines and lean-burn engines.

A New Control Strategy for Air/Fuel Regulation of Spark Ignition Engines to Maximize Energy Economy and Minimize Environment Pollution

The gasoline for cars and light trucks accounts for more than 40% of the total oil consumption worldwide. More important is the environment subjected to the pollution emitted by spark ignition engine's tailpipe. Spark ignition engines are commonly equipped with electronic control systems whose task is to provide desired air-fuel ratio (AFR) signal tracking to improve fuel energy economy and reduce exhaust emissions. The engine control system maintains the AFR to be close to the stoichiometric value as an index of maximum catalytic convertor efficiency. Unfortunately, performance of the catalytic convertor significantly depends on the precise value of the AFR. For instance, exceeding the stoichiometric value by 1% results in about 50% higher NOx emissions while receding the stoichiometric value by 1% drastically increases CO and HC pollutants. In addition to the emission concerns, regulated AFR according to the stoichiometric value can improve the fuel economy and provide efficient torque demands. However, the wide engine operating range, the inherent nonlinearities of the combustion process, the large modelling uncertainties and parameter variations along with the time-varying delay in the spark ignition engines make the design of the control system a challenging task. In this paper, we present a new synthesis method to control air-fuel ratio (AFR) in spark ignition engines to maximize the fuel energy economy while minimizing environment pollutants (exhaust emissions). In this paper the time-varying delay is rendered into non-minimum phase characteristics with time-varying parameters. Application of parameter-varying dynamic compensators is invoked to retrieve unstable internal dynamics. Associated error dynamics is then utilized to construct a parameter-varying proportional-integral-derivative (PID) controller combined with a parameter-varying dynamic compensator to track the desired AFR command using the feedback from the universal exhaust gas oxygen sensor. The proposed method achieves desired dynamic properties independent of the matched and unmatched disturbances due to the dynamic compensator features. Results of applying the proposed method to experimental data on a Ford truck F-150 with a V8 4.6L engine demonstrate the closed-loop system excellent stability and performance against time-varying delay, canister purge disturbances and measurement noise for both port fuel injection engines and lean-burn engines.

The Research of Air Fuel Ratio Self-Learning Control Strategy Based on UEGO Sensor

This paper begins with physical characteristics and the basic working principle of the traditional switch-type Exhaust Gas Oxygen (EGO) sensor and Universal Exhaust Gas Oxygen (UEGO) senor, and then it analyses the Air-Fuel ratio (A/F) Self-learning Control strategy and designs A/F Self-learning Control algorithm of Electronic Control Turbocharged CNG lean-burn engine based on UEGO sensor. At the end, it uses the written control code into ECU of the test engine, and after bench calibration tests it shows that the designed algorithm can compensate wearing, tiring, aging and other state of the engine and improve A/F control accuracy.

Lean Gasoline Engine Reductant Chemistry During Lean NOx Trap Regeneration

Lean Gasoline Engine Reductant Chemistry During Lean NOx Trap Regeneration

Misfire-misfuel classification using support vector machines

This paper proposes the use of support vector machines to perform classification between different types of missed combustion event in a six-cylinder engine. On-board diagnostics regulations require the detection of missed combustion events, which is possible through interpretation of crankshaft speed information. However, current approaches provide no information on the actual cause of the event, in particular whether it was caused by a misfuel (absence of fuel) or a misfire (absence of spark) event. Whilst the impact on the environment and emission treatment systems due to misfuel is minimal, misfire events are detrimental to both. Consequently information regarding the causes of missing combustion events potentially allows the development of unique recovery strategies particular to the source of the problem. In this paper, an approach is proposed that will provide the potential for, firstly, detection of a missing combustion event and, secondly, real-time classification of the event into either misfuel or misfire events using feedback from a heated universal exhaust gas oxygen sensor. In order to evaluate the potential of such a system in an engine control unit, a computational complexity measure is also presented.

全領域空燃比センサ他エンジン制御センサ

This paper describes the operating principles, characteristics, reliability, applications, and features of sensors used in emission control for gasoline engines, such as exhaust gas oxygen sensors, universal exhaust gas oxygen sensors, and NOx sensors. Additionally it describes technical trends in emission control systems for diesel engines and such sensors as temperature sensors, NH3 sensors, and soot sensors.

Measurements of cycle resolved air-fuel ratio near the spark plug in a spark ignition engine

Mixture preparation is a key contributor to both the combustion and emissions of the automotive gasoline engine. The air-fuel ratio near the spark plug may have an effect on combustion characteristics, especially at low load, since it is related to flame development. Therefore, measurements of the cycle-resolved equivalence ratio near the spark plug are particularly important for a better understanding of their contribution to combustion and emissions. This paper describes how the in-cylinder equivalence ratio was determined from the measured hydrocarbon concentrations near the spark plug using a fast response flame ionization detector (FRFID). The procedures established were then applied to a limited range of engine operating conditions, and the cycle-resolved equivalence ratio near the spark plug was determined from the measured hydrocarbon concentration. The results showed that with premixed propane fuel the cyclic variation in equivalence ratio near the spark plug was quite small and corresponded to the overall equivalence ratio from the universal exhaust gas oxygen (UEGO) sensor signal. However, with gasoline fuel the equivalence ratio near the spark plug varied by up to 10 per cent and did not coincide with the UEGO sensor signal on a cyclic basis. The variation in equivalence ratio near the spark plug affected the heat release rate, which in turn affected the indicated mean effective pressure (i.m.e.p.). The equivalence ratio excursions and its effects during acceleration and deceleration are strongly related to the exhaust emissions, fuel economy and so on. With this in mind, the quantitative measurement method using the measured hydrocarbon concentrations was studied for detailed analysis during transient conditions. It was also observed that cyclic variation in the equivalence ratio near the spark plug might be one cause of cycle-by-cycle variation.