Rasoul Salehi

Control oriented modeling of a radial turbine for a turbocharged gasoline engine

This paper presents a control oriented model for predicting turbine major variables in a turbocharged spark ignition engine. The turbine is simulated as a two-nozzle chamber where the pressure ratio over the two nozzles is not the same. A convex nonlinear estimation algorithm is formulated to determine the relation between these pressure ratios. The new model is experimentally validated with transient and steady state data collected from a 1.7 liter gasoline engine. The results show the new model can predict the turbine mass flow with an average error of 1.4%. In addition, the application of the turbine model is illustrated for the design of a nonlinear observer to estimate the turbocharger non-measured variables. The designed observer is tested against experimental data and the results confirm the observer capability to estimate the turbine rotor speed, flow over the compressor and temperature downstream the compressor.

A Second-Order Sliding Mode Observer for Fault Detection and Isolation of Turbocharged SI Engines

This paper proposes a novel method for detection and isolation of wastegate (WG) faults in a turbocharged (TC) gasoline engine. This paper starts with a fault effect analysis on the WG faults, including WG stuck open and stuck closed, which is an early step in a detection strategy design. Then, a second-order sliding-mode observer (SOSMO) is proposed to capture the exhaust manifold dynamics. The observer uses experimentally validated engine models to estimate the WG position and a virtual force. The virtual force represents the external disturbances that disrupt the WG operation and enables the proposed SOSMO to estimate the WG position robust to the faults. Using this force, a detection and isolation algorithm is presented and experimentally verified on a modern TC gasoline engine. Test bench results show that the proposed strategy can successfully detect and isolate the two different WG faults.

Hybrid switching control of automotive cold start hydrocarbon emission

Reduction of cold start hydrocarbon (HC) emission requires a proper compromise between low engine-out HC emission and fast light-off of the three way catalytic converter (TWC). In this paper a model based approach is used to design and optimize a hybrid switching system for reducing HC emission of a mid-sized passenger car during the cold start phase of FTP-75. This hybrid system takes the benefit of increasing TWC temperature during the early stages of the driving cycle by switching between different operational modes. The switching times are optimized to reduce the cumulative tailpipe HC emission of an experimentally validated automotive emission model. It is shown that the new hybrid system can reduce cold start HC emissions by 7.5% to 52.5% compared to traditional single mode control approaches.

Real-Time Estimation of the Volumetric Efficiency in Spark Ignition Engines Using an Adaptive Sliding-Mode Observer

Proper operation of an engine requires accurate measurement or estimation of the engine’s air charge provided to the control unit which reduces both the engine’s fuel consumption and the emissions. The volumetric efficiency of the engine is a key variable in computations using the engine control unit to estimate the air charge using the speed–density equation. This paper presents a new approach for real-time estimation of the volumetric efficiency using the sliding-mode methodology. An adaptive sliding-mode observer is proposed which relies on measurements from the engine’s conventional sensors. The observer is shown to estimate asymptotically the volumetric efficiency of the engine for different operating conditions. A method for eliminating the chattering effects caused by the sign function in the estimation of the volumetric efficiency, which improves the performance of the sliding-mode observer in terms of the accuracy and the response time, is also given. The experimental results from a modern spark ignition engine show a good performance of the sliding-mode observer for estimating the engine air charge compared with the measured data.

Model-based air leak detection for turbocharged gasoline engines without a hot-film air mass flow meter sensor

This paper presents an observer-based fault detection and isolation strategy to detect and isolate an air leakage in the compressor–throttle path and a fault in the boost pressure sensor in a turbocharged gasoline engine. The strategy is applicable to engines not equipped with a hot-film air mass flow meter sensor. A novel combination of a turbocharger model and a control volume model for the pressure dynamics of the intercooler is used to design an asymptotically stable non-linear observer which estimates the unmeasured turbocharger variables. The turbocharger observer’s estimation error is used as a residual in the fault detection and isolation process where the effects of the measurement noise and the model simplifications are cancelled using the maximum-likelihood ratio as the test statistic. An engine charge estimation observer is added to the turbocharger observer for detection and isolation of the air leakage from the sensor fault. Validation of all models and the fault detection and isolation strategy is carried out for a modern gasoline turbocharged engine. The experimental results reveal the ability of the control-oriented strategy to perform online detection and isolation of air leakage through a hole with a diameter of 5 mm or larger.

Modeling and Estimation of Unmeasured Variables in a Wastegate Operated Turbocharger

Estimation of relevant turbocharger variables is crucial for proper operation and monitoring of turbocharged (TC) engines, which are important in improving fuel economy of vehicles. This paper presents mean-value models developed for estimating gas flow over the turbine and the wastegate (WG), the wastegate position, and the compressor speed in a TC gasoline engine. The turbine is modeled by an isentropic nozzle with a constant area and an effective pressure ratio calculated from the turbine upstream and downstream pressures. Another physically sensible model is developed for estimating either the WG flow or position. Provided the WG position is available, the WG flow is estimated using the orifice model for compressible fluids. The WG position is predicted considering forces from the WG passing flow and actuator. Moreover, a model for estimating the compressor speed in low and medium compressor pressure ratios is proposed, using the compressor head and efficiency modified by the turbine effective pressure ratio. The estimates of the turbocharger variables match well with the experimentally measured data. The three proposed models are simple in structure, accurate enough to be utilized for engine modeling, and suitable to be validated and calibrated on an internal combustion engine in a test cell.

Nonlinear observer design for turbocharger in a SI engine

Estimation of major turbocharger variables is essential for proper control and monitoring of a turbocharged engine. This work presents a novel algorithm to estimate turbocharger rotator speed, air temperature downstream a compressor and flow rate over the compressor using mean value models of engine subsystems. A nonlinear Luenberger observer is designed for a 1.7-lit gasoline turbocharged engine. The designed observed is shown analytically to be asymptotically stable. Performance of the designed observer is experimentally validated with the data collected from the engine. The results indicate the observer can capture major turbochargers rotational dynamics and estimated turbocharger variables are in a good agreement with the experimental measurements.

On-Line Fault Detection and Isolation (FDI) for the Exhaust Path of a Turbocharged SI Engine

Detection and isolation of faults in the exhaust gas path of a turbocharged spark ignition (SI) engine is an essential part of the engine control unit (ECU) strategies to minimize exhaust emission and ensure safe operation of a turbocharger. This paper proposes a novel physics-based strategy to detect and isolate an exhaust manifold leakage and a closed-stuck wastegate fault. The strategy is based on a globally optimal parameter estimation algorithm which detects an effective hole area in the exhaust manifold. The estimation algorithm requires prediction of the exhaust manifold’s input and output flows. The input flow is predicted by a nonlinear Luenberger observer which is analytically shown to be robust to the faults in the exhaust manifold. The output flow of the exhaust manifold is detected by a sliding mode observer. The designed fault diagnosis and isolation (FDI) strategy is tested with the experimental data collected from a 1.7-liter turbocharged SI engine. The validation results show that the FDI strategy can detect a leakage fault from a 5mm hole in the exhaust manifold, and can identify the wastegate stuck faults.Copyright

Fault effect analysis of the exhaust manifold leakage for a turbocharged spark ignition engine

Fault monitoring in internal-combustion engines is crucial for keeping the vehicle performance within the acceptable standards of emission levels and drivers’ demands. This paper analyses how a vehicle’s performance and engine variables are affected by a leakage fault in the exhaust manifold. The threshold leakage that causes the vehicle to exceed the emission standards is determined for a class M1 vehicle tested on a chassis dynamometer over the New European Driving Cycle. It is shown that, when a leakage of 6 mm diameter on the exhaust manifold is introduced, the vehicle emissions exceed those specified in the European 2013 on-board diagnostics standard. In addition, the effects of the said leakage fault on the performance of a 1.7 l turbocharged gasoline engine are analysed at different speed–torque operating points by running the engine in a test cell. The results show that, for this 6 mm leakage, at most operating points the driver cannot notice any reduction in the engine torque. Using the engine performance analysis, a fault effect map for the turbocharged gasoline engine is obtained. This helps to design monitoring algorithms for detection of the exhaust manifold leakage fault. As an application of the map, a strategy is presented on the basis of a comparison between the measured and the estimated pressures downstream of the turbine for the purpose of detecting the exhaust manifold leakage.

Designing Gear-Shift Pattern for an Electric Vehicle to Optimize Energy Consumption

In this paper optimization of energy consumption in an electric vehicle is presented. The main idea of this optimization is based on selecting the best gear level in driving the vehicle. Two algorithms for optimization are introduced which are based on fuzzy rules and fuzzy controllers. In first algorithm, fuzzy controller simulates energy consumption in different gear levels, and chooses the optimum gear level. While in second method, fuzzy controller detects the optimum gear level by measuring the vehicle’s average speed and acceleration. To investigate the performance of these controllers, a model of TOSAN vehicle is developed and the controllers outputs are checked in simulation of TOSAN being driven within drive cycles in the city of Tehran. It is shown that both algorithms are able to improve efficiency in typical city driving cycles.Copyright