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Recent automotive technological advancements mainly focus on improving fuel economy with satisfactory emissions, leading to significant increment of engine system complexity, especially for diesel engines. This results in a large number of calibration parameters in control features, making the engine calibration process a challenge and time consuming using the conventional map-based approach. This article proposes a methodology to perform engine calibration using surrogate assisted optimization to reduce calibration effort for diesel engines. A high fidelity GT-Power engine model is used for the current calibration study. The objective is to find the tradeoff relationship between engine efficiency (brake specific fuel consumption) and its NOx emissions. Both these objectives are optimized by calibrating three control variables—namely, variable geometry turbocharger vane position, exhaust-gas-recirculating valve position, and the start of injection. Kriging surrogate models are developed for both objectives and constraints, where lower confidence bound is used as an acquisition function with a newly proposed constraint handling method and nondominated sorting algorithm is used for performing optimization. Results from this proposed algorithm demonstrate that the optimal points obtained for both test and actual engine calibration problems are pretty close to their true Pareto optimal front. For the engine calibration problem, more than 85% reduction in total computational budget is observed. Preliminary experimental study results are also presented to compare them with the simulation results, and the optimal tradeoff from both of them indicates a similar trend. [ABSTRACT FROM AUTHOR]

An extended adaptive cruise control (ACC), called economic adaptive cruise control, is proposed to improve the fuel economy for power split hybrid electric vehicles (HEV) by optimizing the vehicle route, speed, and powertrain control simultaneously. The economic route and speed for a given origin-destination pair with the given expected trip time are optimized by a proposed vehicle macroscopic motion planning method, where the powertrain is optimized by a proposed global power distribution (GPD) strategy. The HEV powertrain controller, consisting of feedforward and feedback control schemes, is developed for real-time cruise control, where the former is based on the GPD strategy and the latter is based on the receding horizon linear quadratic tracking method. In addition, a mode-switch local optimization method is used to modify the reference speed for passing, traffic jam and light crossing. A co-simulation model, combining the SUMO traffic model and Simulink hybrid powertrain model, is developed and used for validating the proposed EACC strategy. The co-simulation results indicate that the proposed EACC is able to decrease the fuel consumption by more than 30% comparing with the power follower strategy adopting the fastest route. Note that even with the same powertrain controller, the economic route and speed stratgey is able to improve the fuel economy by 14.21%, comparing with the fastest route without optimization. [ABSTRACT FROM AUTHOR]

This paper presents an optimal tracking control of engine valve timing for an electro-hydraulic variable valve actuator utilizing the adaptively estimated supply pressure that is the main source for valve timing variation. The system supply pressure is online estimated through a model-guided adaptive estimator with one-step prediction capability. The estimation model consists of a static guidance model, an in-event valve model, and a one-step prediction model. Using the estimation model, the adaptive estimator generates a nominal estimation with accelerated convergence, estimates the pressure residual error using in-event dynamics, and provides one-step forward pressure prediction along with the resulting pressure fluctuation. The linear quadratic tracking (LQT) control is used to track the desired valve timing based on an event-by-event valve model, where the adaptively estimated pressure variation is used as the feedforward control in the LQT control to improve the tracking accuracy and a Kalman filter is used to estimate the system states for the LQT state feedback control. The parameter estimation and control algorithms are validated through both the simulation and test bench studies by comparing different estimation and control schemes. Both the steady-state and transient operational conditions are investigated, and the effectiveness of the proposed adaptive LQT valve timing control is demonstrated. [ABSTRACT FROM AUTHOR]

The camless valve system is able to provide flexible engine-valve profiles (timing, duration, lift, etc.) to optimize the performance of internal combustion engines. To provide a precise valve profile of an electro-hydraulic variable valve actuator and achieve the desired engine performance, an optimal tracking controller for the valve-rising duration, a key valve profile parameter, is presented in this paper. An event-by-event nonlinear model, connecting the system supply pressure dynamics to the valve-rising duration, is developed and linearized along the desired valve-rising trajectory. Based on the trajectory linearization, a receding horizon linear–quadratic tracking (LQT) controller is designed along with a Kalman optimal state estimation. The equilibrium control resulted from the model linearization is used as the LQT feedforward control. The control performance is compared with that of baseline controllers through both simulation study and bench tests. The transient and steady-state validation results confirm the effectiveness of proposed control scheme. [ABSTRACT FROM AUTHOR]

This paper presents experimental investigation results of an electric variable valve timing (EVVT) actuator using linear parameter varying (LPV) system identification and control. For the LPV system identification, a number of local system identification tests were carried out to obtain a family of linear time-invariant (LTI) models at fixed engine speed and battery voltage. Using engine speed and battery voltage as time-varying scheduling parameters, the family of local LTI models is translated into a single LPV model. Then, a robust gain-scheduling (RGS) dynamic output-feedback (DOF) controller with guaranteed H∞ performance was synthesized and validated experimentally. In contrast to the vast majority of gain-scheduling literature, scheduling parameters are assumed to be polluted by measurement noises and the engine speed and battery voltage are modeled as noisy scheduling parameters. Experimental and simulation results show the effectiveness of the developed approach. [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]

Engine electronic throttle control (ETC) is challenging due to its high system nonlinearities and the required fast response time. In this paper, an electronic throttle system was modeled as a linear parameter varying (LPV) system in discrete-time domain, where the vehicle battery voltage is modeled as the measurable time-varying parameter; the nonlinear friction is modeled as a function of the measurable throttle position; and the limp-home spring nonlinearity is compensated through feedforward control. Mixed constrained ${{H_2}/{H_\infty}}$ LPV controller was designed for the LPV throttle control system using the linear matrix inequality convex optimization approach. The system output and control weights were optimized through simulation studies to achieve the best performance; and the finalized LPV controller was experimentally validated on an ETC test bench. Comparing with the baseline well-tuned fixed gain proportional, integral, and derivative controller, the LPV controller reduces the 2% settling time from 0.30 to 0.15 s. Especially, smooth transient response was achieved when the throttle plate crosses the region with heavy spring nonlinearity required by the limp-home operation. [ABSTRACT FROM PUBLISHER]

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]

The combustion mode transition between spark ignition (SI) and homogeneous charge compression ignition (HCCI) combustion of an internal combustion (IC) engine is challenging due to the distinct engine operating parameters over the two combustion modes and the cycle-to-cycle residue gas dynamics during the mode transition. The control problem becomes even more complicated for a multicylinder engine without camless variable valve actuators. This paper studies the combustion mode transition problem of a multicylinder IC engine equipped with dual-stage valve lift and electrical variable valve timing (VVT) systems. Hardware-in-the-loop (HIL) simulations were used as a tool to develop and validate the proposed control strategies. Based on the HIL simulation results, this paper shows that smooth combustion mode transition can be realized in a few engine cycles. During the mode transition, a model-based linear quadratic tracking strategy was used to track the desired engine manifold pressure through the engine throttle control to maintain the engine AFR in a desired range; the fuel quantity of individual cylinder was controlled via the iterative learning; and engine spark was maintained for the SI–HCCI (or spark assistant) hybrid combustions during the combustion mode transition. The HIL simulations demonstrated the effectiveness of the developed control strategies under both steady state and transient engine operating conditions. As a result, it is feasible to have a smooth combustion mode transition for an HCCI capable SI engine equipped with dual-stage valve lift and electrical VVT systems. [ABSTRACT FROM AUTHOR]

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]

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]

This paper presents a methodology of calculating the optimal torque and speed commands for the engine–generator system of a series hybrid electric vehicle (HEV). In series HEVs, the engine–generator subsystem provides electrical energy to the dc link. This paper proposes an optimal control strategy of the engine–generator subsystem to generate a desired amount of energy within a given period of time. The optimization algorithm, based on trajectory optimization, determines the torque and speed reference signals for the engine–generator subsystem that achieve maximum efficiency. A simplified version of the controller is also presented for online implementation. The proposed control strategy is compared with nonoptimized control techniques, and simulation results show the improvements in energy efficiency. [ABSTRACT FROM PUBLISHER]

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]

Minimal advance for best torque (MBT) timing for an internal combustion (IC) spark ignition (SI) engine is the minimum advance of spark timing for the best torque or, in other words, for the best fuel economy. But MBT timing is often limited by engine knock in the advanced direction and spark timing is also constrained by partial burn and misfire in the retard direction. It is preferred to operate IC engines at MBT timing when it is not knock limited and at borderline knock limit when it is knock limited. During cold start conditions it is desired to operate IC engines at its maximum retard limit subject to combustion stability constraints to reduce catalyst light-off time. Traditionally, both MBT timing and retard spark limit are open-loop feedforward controls whose values are experimentally determined by conducting spark sweeps at different speed and load points, and at different environmental conditions. The borderline knock limit is controlled by a dual-rate count-up/count-down closed-loop control utilizing in- formation from engine knock sensor signals. A closed-loop control architecture for spark timing is proposed in this paper. Using in-cylinder ionization signals both borderline knock and retard spark limits are regulated using closed-loop stochastic limit controls. MBT timing is also controlled closed-loop using an MBT criterion derived from in-cylinder ionization signals. The proposed control strategy and architecture was experimentally validated on a 3.0-L V6 engine for steady state and slow transient conditions. [ABSTRACT FROM AUTHOR]

While the homogeneous charge compression ignition (HCCI) combustion has its advantages of high thermal efficiency with low emissions, its operational range is limited in both engine speed and load. To utilize the advantage of the HCCI combustion, an HCCI capable spark ignition (SI) engine is required. One of the key challenges of developing such an engine is to achieve smooth mode transition between SI and HCCI combustion, where the in-cylinder thermal and charge mixture properties are quite different due to the distinct combustion characteristics. In this paper, a control strategy for smooth mode transition between SI and HCCI combustion is developed and experimentally validated for an HCCI capable SI engine equipped with electrical variable valve timing (EVVT) systems, dual-lift valves, and electronic throttle control (ETC) system. During the mode transition, the intake manifold air pressure is controlled by tracking the desired throttle position updated cycle-by-cycle; and an iterative learning fuel mass controller, combined with sensitivity-based compensation, is used to manage the engine torque in terms of net mean effective pressure (NMEP) at the desired level for smooth mode transition. Note that the NMEP is directly correlated to the engine output torque. Experiment results show that the developed controller is able to achieve smooth combustion mode transition, where the NMEP fluctuation is kept below 3.8% during the mode transition. [ABSTRACT FROM AUTHOR]

A surrogate-assisted optimization approach is an attractive way to reduce the total computational budget for obtaining optimal solutions. This makes it special for its application to practical optimization problems requiring a large number of expensive evaluations. Unfortunately, all practical applications are affected by measurement noises, and not much work has been done to address the issue of handling stochastic problems with multiple objectives and constraints. This work tries to bridge the gap by demonstrating three different frameworks for performing surrogate-assisted optimization on multi-objective constrained problems with stochastic measurements. To make the algorithms applicable to real-world problems, heteroscedastic (nonuniform) noise is considered for all frameworks. The proposed algorithms are first validated on several multi-objective numerical problems (unconstrained and constrained) to verify their effectiveness and then applied to the diesel engine calibration problem, which is expensive to perform and has measurement noises. A gt-suite model is used to perform the engine calibration study. Three control parameters, namely, variable geometry turbocharger (VGT) vane position, exhaust-gas-recirculating (EGR) valve position, and the start of injection (SOI), are calibrated to obtain the tradeoff between engine fuel efficiency performance (brake specific fuel consumption (BSFC)) and NOx emissions within the constrained design space. The results show that all three proposed extensions can handle the problems well with different measurement noise levels at a reduced evaluation budget. For the engine calibration problem, a good approximation of the optimal region is observed with more than 80% reduction in the evaluation budget for all the proposed methodologies. [ABSTRACT FROM AUTHOR]

Engine downsizing and down-speeding are essential in order to meet future U.S. fuel economy (FE) mandates. Turbocharging is one technology to meet these goals. Fuel economy improvements must, however, be achieved without sacrificing performance. One significant factor impacting drivability on turbocharged engines is typically referred to as "turbolag." Since turbolag directly impacts the driver's torque demands, it is usually perceptible as an undesired slow transient boost response or as a sluggish torque response. High throughput turbochargers (TC) are especially susceptible to this dynamic and are often equipped with variable geometry turbines (VGT) to mitigate some of this effect. Assisted boosting techniques that add power directly to the TC shaft from a power source that is independent of the engine have been shown to significantly reduce turbolag. Single unit assisted turbochargers are either electrically assisted or hydraulically assisted. In this study, a regenerative hydraulically assisted turbocharger (RHAT) system is evaluated. A custom-designed RHAT system is coupled to a light duty diesel engine and is analyzed via vehicle and engine simulations for performance and energy requirements over standard test cycles. Supplier-provided performance maps for the hydraulic turbine, hydraulic turbopump were used. A production controller was coupled with the engine model and upgraded to control the engagement and disengagement of RHAT, with energy management strategies. Results show some interesting dynamics and shed light on system capabilities especially with regard to the energy balance between the assist and regenerative functions. Design considerations based on open-loop simulations are used for sizing the high-pressure accumulator. Simulation results show that the proposed RHAT turbocharger system can significantly improve engine transient response. Vehicle level simulations that include the driveline were also conducted and showed potential for up to 4% fuel economy improvement over the FTP 75 drive cycle. This study also identified some technical challenges related to optimal design and operation of the RHAT. Opportunities for additional fuel economy improvements are also discussed. [ABSTRACT FROM AUTHOR]