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The increasing concerns of air pollution and energy usage led to the electrification of the vehicle powertrain system in recent years. On the other hand, internal combustion engines were the dominant vehicle power source for more than a century, and they will continue to be used in most vehicles for decades to come; thus, it is necessary to employ advanced technologies to replace traditional mechanical systems with mechatronic systems to meet the ever-increasing demand of continuously improving engine efficiency with reduced emissions, where engine intake and the exhaust valve system represent key subsystems that affect the engine combustion efficiency and emissions. This paper reviews variable engine valve systems, including hydraulic and electrical variable valve timing systems, hydraulic multistep lift systems, continuously variable lift and timing valve systems, lost-motion systems, and electro-magnetic, electro-hydraulic, and electro-pneumatic variable valve actuation systems. [ABSTRACT FROM AUTHOR]

Hybrid electric vehicles (HEVs) are capable of improving fuel economy with reduced emissions over traditional vehicles powered only by the internal combustion (IC) engine. HEV durability is often significantly limited by the useful life of the battery, and battery life can be significantly reduced if the battery is often operated outside its allowed discharging/charging limits. This could occur particularly at extremely low temperature, leading to permanent damage and reduced useful life of the battery. To reduce battery overdischarging duration for extended battery life, this paper proposes a stochastic predictive boundary management (SPBM) strategy to proactively make the engine power available to the powertrain based on the predicted torque requirement and its prediction error variance. The effectiveness of the proposed SPBM is validated in simulations, and its performance is compared with the baseline power follower control strategy (PFCS) and predictive boundary management (PBM) under five typical driving cycles with selected initial battery temperature. The simulation results show that the proposed control strategy dramatically reduces the battery overdischarging energy under all five typical driving cycles over both PFCS and PBM, where the average reduction is 82% under aggressive US06 and ARB02 driving cycles, 67% under NYCC and FTP driving cycles, and 37% under the IM240 highway driving cycle. Note that the adaptive prediction and its error variance can be calculated in real time with fairly low computational load. [ABSTRACT FROM PUBLISHER]

Hybrid powertrain provides driving torque based upon the vehicle acceleration pedal position. Due to the slow response of the internal combustion (IC) engine, the electric motor(s) (EM) often has to provide additional torque during transient vehicle operations. During cold-start operations, the available battery power is significantly reduced due to cold temperatures, and due to the starting delay of the IC engine, the battery has to provide power at the level beyond its normal operation limit for the electrical motor to meet the torque demand, which would dramatically shorten the battery life. However, if the desired powertrain torque can be predicted, the IC engine could be started early when the predicted future powertrain power is higher than the battery normal operational range, and hence, the duration of battery operated over its normal operational range could be significantly reduced, leading to extended battery life. This makes predicting multistep future torque demand, based upon current and past torque demand data, an important subject. Amid many existing studies, few research studies were focused on this subject. This paper proposes an adaptive recursive prediction algorithm to estimate the future desired powertrain torque and compares the performance of the proposed algorithm with two existing prediction algorithms, i.e., step-by-step and fixed-gain algorithms. These three prediction algorithms are studied under the federal test procedure (FTP) and another four typical driving cycles. The simulation results show that the adaptive recursive prediction algorithm reduces the prediction error significantly with a 4% maximum prediction error, and in addition, the reduced computational load makes it feasible for real-time implementation. The introduced weighting factors for the past and current data are the key to improve prediction accuracy and avoid prediction calculation over- and underflow. In addition, due to the online update of regression gain, the proposed algorithm is also robust to driving behavior variations. [ABSTRACT FROM PUBLISHER]

Modern spark ignited (SI) internal combustion engines maintain their air-to-fuel ratio (AFR) at a desired level to maximize the three-way catalyst conversion efficiency and du-rability. However, maintaining the engine AFR during its transient operation is quite challenging due to rapid changes of driver demand or engine throttle. Conventional tran-sient AFR control is based upon the inverse dynamics of the engine fueling dynamics and the measured mass air flow (MAF) rate to obtain the desired AFR of the gas mixture trapped in the cylinder. This paper develops a linear quadratic (LQ) tracking controller to regulate the transient AFR based upon a control-oriented model of the engine port fuel injection (PFI) wall wetting dynamics and the air intake dynamics from the measured air-flow to the manifold pressure. The LQ tracking controller is designed to optimally track the desired AFR by minimizing the error between the trapped in-cylinder air mass and the product of the desired AFR and fue I mass over a given time interval. The performance of the optimal LQ tracking controller was compared with the conventional transient fuel-ing control based on the inverse fueling dynamics through simulations and showed improvement over the baseline conventional inverse fueling dynamics controller. To vali-date the control strategy on an actual engine, a 0.4 I single cylinder direct-injection (DI) engine was used. The PFI wall wetting dynamics were simulated in the engine controller after the DI injector control signal. Engine load transition tests for the simulated PFI case were conducted on an engine dynamometer, and the results showed improvement over the baseline transient fueling controller based on the inverse fueling dynamics. [ABSTRACT FROM AUTHOR]

A control-oriented engine model is often used in the hardware-in-the-loop (HIL) simulation environment for developing and validating the corresponding control strategies. For homogeneous charge compression ignition (HCCI) combustion, mixture heterogeneity should be considered in the control-oriented model to provide accurate combustion phase prediction. This paper describes a two-zone HCCI combustion model, where the in-cylinder charge is divided into the well-mixed and unmixed zones as the result of charge mixing. Simplified fluid dynamics is used to predict the residual gas fraction before the combustion phase starts, which defines the mass of the unmixed zone, during real-time simulations. The unmixed-zone size determines not only how well the in-cylinder charge is mixed, which affects the start of HCCI combustion, but also the resulting peak in-cylinder pressure and temperature during the combustion process. The developed model was validated in the HIL simulation environment. The HIL simulation results show that the proposed charge mixing and HCCI combustion model provides better agreement with the corresponding GT-Power simulation results than the previously developed one-zone model. [ABSTRACT FROM PUBLISHER]

In this paper, a family of linear models previously obtained from a series of closed-loop system identification tests for a variable valve timing cam phaser system is used to design a dynamic gain-scheduling controller. Using engine speed and oil pressure as the scheduling parameters, the family of linear models was translated into a linear parameter varying (LPV) system. An observer-based gain-scheduling controller for the LPV system is then designed based on the linear matrix inequality technique. A discussion on weighting function selection for mixed \cal H2/\cal H\infty controller synthesis is presented, with an emphasis placed on examining various frequency responses of the system. Test bench results show the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

A multi-input-multi-output (MIMO) sliding mode control scheme was developed with guaranteed stability to simultaneously control air-to-fuel ratio (AFR) and fuel ratios to desired levels under various air flow disturbances by regulating the mass flow rates of engine port-fuel-injection (PFI) and direct injection (DI) systems. The sliding mode control peiformance was compared with a baseline multiloop proportional integral differential (PID) controller through simulations and showed improvements. A four cylinder mean value engine model and the proposed sliding mode controller were implemented into a hardware-in-the-loop (HIL) simulator and a target engine control module, and HIL simulations were conducted to validate the developed controller for potential implementation in an automotive engine. [ABSTRACT FROM AUTHOR]

In this paper, an event-based sampled discrete-time linear system representing a port-fuel-injection process based on wall-wetting dynamics is obtained and formulated as a linear parameter varying (LPV) system. The system parameters used in the engine fuel system model are engine speed, temperature, and load. These system parameters can be measured in real time through physical or virtual sensors. A gain-scheduling controller for the obtained LPV system is then designed based on the numerically efficient convex optimization or linear matrix inequality (LMI) technique. A hardware-in-the-loop (HIL) simulation is performed to validate the gain-scheduling controller on a mixed mean-value and crank-based engine model. The HIL simulation results show the effectiveness of the proposed gain-scheduling controller. [ABSTRACT FROM AUTHOR]

Electro-pneumatic valve actuators are used to eliminate the cam shafts of a traditional internal combustion engine. They are used to control the opening timing, duration, and lift of both intake and exhaust valves. In order to develop model-based control strategies, a control oriented model was developed by piecewisely linearizing the physics-based nonlinear system model. In this paper, an adaptive valve lift control strategy was developed to improve the intake valve lift repeatability. The model reference adaptive system identification technique was employed to estimate system parameters needed for generating feedforward control signals for the closed-loop control scheme. The closed-loop lift control strategies, along with the model reference feedforward control, were developed and implemented in a prototype controller, and validated on a valve test bench with multiple reference valve lifts at both 1200 and 5000 r/min engine speeds. The experiment results showed that the actual valve lift reached the reference lift within 0.5 mm of lift error in one cycle at 1200 r/min and in two cycles at 5000 r/min. The maximum steady-state lift errors were less than 0.4 mm at high valve lift and less than 1.3 mm at low valve lift. Furthermore, the closed-loop valve lift control improved valve lift repeatability with more than 30% reduction of standard deviation over the open-loop control. [ABSTRACT FROM AUTHOR]

This paper presents a detailed model of a novel electropneumatic valve actuator for both engine intake and exhaust valves. The valve actuator's main function is to provide variable valve timing and variable lift capabilities in an internal combustion engine. The pneumatic actuation is used to open the valve and the hydraulic latch mechanism is used to hold the valve open and to reduce valve seating velocity. This combination of pneumatic and hydraulic mechanisms allows the system to operate under low pressure with an energy saving mode. It extracts the full pneumatic energy to open the valve and use the hydraulic latch that consumes almost no energy to hold the valve open. A system dynamics analysis is provided and followed by mathematical modeling. This dynamic model is based on Newton's law, mass conservation, and thermodynamic principles. The air compressibility and liquid compressibility in the hydraulic latch are modeled, and the discontinuous nonlinearity of the compressible flow due to choking is carefully considered. Provision is made for the nonlinear motion of the mechanical components due to the physical constraints. Validation experiments were performed on a Ford 4.6 l four-valve V8 engine head with different air supply pressures and different solenoid pulse inputs. The simulation responses agreed with the experimental results at different engine speeds and supply air pressures. [ABSTRACT FROM AUTHOR]