Real-time optimal energy management of electrified engines

© 2016 The electrification of engine components offers significant opportunities for fuel economy improvements, including the use of an electrified turbocharger for engine downsizing and exhaust gas energy recovery. By installing an electrical device on the turbocharger, the excess energy in the air system can be captured, stored, and re-used. This new configuration requires a new control structure to manage the air path dynamics. The selection of optimal setpoints for each operating point is crucial for achieving the full fuel economy benefits. In this paper, a control-oriented model for an electrified turbocharged diesel engine is analysed. Based on this model, a structured approach for selecting control variables is proposed. A model-based multi-input multi-output decoupling controller is designed as the low level controller to track the desired values and to manage internal coupling. An equivalent consumption minimization strategy is employed as the supervisory level controller for real-time energy management. The supervisory level controller and low level controller work together in a cascade which addresses both fuel economy optimization and battery state-of-charge maintenance. The proposed control strategy has been successfully validated on a detailed physical simulation model

Decoupling control of electrified turbocharged diesel engines

Engine electrification is a critical technology in the promotion of engine fuel efficiency, among which the electrified turbocharger is regarded as a promising solution for its advantages in engine downsizing and exhaust gas energy recovery. By installing electrical devices on the turbocharger, the excess energy can be captured, stored, and re-used. The control of the energy flows in an electrified turbocharged diesel engine (ETDE) is still in its infancy. Developing a promising multi-input multi-output (MIMO) control strategy is essential in exploring the maximum benefits of electrified turbocharger. In this paper, the dynamics in an ETDE, especially the couplings among multiple loops in the air path are analyzed. Based on the analysis, a model-based MIMO decoupling control framework is designed to regulate the air path dynamics. The proposed control strategy can achieve fast and accurate tracking on selected control variables and is successfully validated on a physical model in simulations

Explicit model predictive control on the air path of turbocharged diesel engines

The turbocharged diesel engine is a typical multi-input multi-output (MIMO) system with strong couplings, actuator constraints, and fast dynamics. This paper addresses the air path regulation in turbocharged diesel engines using an explicit model predictive control (EMPC) approach, which allows tracking of the time-varying setpoint values generated by the supervisory level controller while satisfying the actuator constraints. The proposed EMPC framework consists of calibration, engine model identification, controller formulation, and state observer design. The proposed EMPC approach has a low computation requirement and is suitable for implementation in the engine control unit (ECU) on board. The experimental results on a turbocharged Cat ® C6.6 diesel engine illustrate that the EMPC controller significantly improves the tracking performance of the exhaust emission variables against the decentralized single-input single-output (SISO) control method

Characterisation, control, and energy management of electrified turbocharged diesel engines

The electrification of engine components offers significant opportunities for fuel efficiency improvements. The electrified turbocharger is one of the most attractive options since it recovers part of the engine exhaust gas mechanical energy to assist boosting. Therefore, the engine can be downsized through improved transient responsiveness. In the electrified turbocharger, an electric machine is mounted on the turbine shaft and changes the air system dynamics, so characterisation of the new layout is essential. A systematic control solution is required to manage energy flows in the hybrid system. In this paper, a framework for characterisation, control, and energy management for an electrified turbocharged diesel engine is proposed. The impacts of the electric machine on fuel economy and air system variables are analysed. Based on the characterisation, a two-level control structure is proposed. A real-time energy management strategy is employed as the supervisory level controller to generate the optimal values of critical variables, while a model-based multi-variable controller is designed as the low level controller to track the values. The two controllers work together in a cascade to address both fuel economy optimisation and battery state-of-charge maintenance. The proposed control strategy is validated on a high fidelity physical engine model. The tracking performance shows the proposed framework is a promising solution in regulating the behavior of electrified engines

Systematic control on energy recovery of electrified turbocharged diesel engines

© 2015 IEEE.Recovering energy from exhaust gas is seen as the promising solution to save fuel consumption of diesel engines, where the key issue in maximizing fuel economy benefits is the management of energy flows in the optimal way. This paper proposes a systematic control strategy on both energy management and air path regulation of an electrified turbocharged diesel engine (ETDE). The Energy management and air path regulation is formulated as a multi-variable online optimization problem with constraints. The equivalent consumption minimization strategy (ECMS) is employed as the supervisory level controller, to calculate the optimal energy flow distribution. An explicit model predictive controller (EMPC) is developed as the low level controller to implement the optimal energy flow distribution. The two controllers work together as cascaded modules in real-time, while simulation results based on a physical model show the superior performance over the conventional distributed single-input single-output (SISO) control method

Model Predictive Control of Modern High-Degree-of-Freedom Turbocharged Spark Ignited Engines with External Cooled EGR

The efficiency of modern downsized SI engines has been significantly improved using cooled Low-Pressure Exhaust Gas Recirculation, Turbocharging and Variable Valve Timing actuation. Control of these sub-systems is challenging due to their inter-dependence and the increased number of actuators associated with engine control. Much research has been done on developing algorithms which improve the transient turbocharged engine response without affecting fuel-economy. With the addition of newer technologies like external cooled EGR the control complexity has increased exponentially. This research proposes a methodology to evaluate the ability of a Model Predictive Controller to coordinate engine and air-path actuators simultaneously. A semi-physical engine model has been developed and analyzed for non-linearity. The computational burden of implementing this control law has been addressed by utilizing a semi-physical engine system model and basic analytical differentiation. The resulting linearization process requires less than 10% of the time required for widely used numerical linearization approach. Based on this approach a Nonlinear MPC-Quadratic Program has been formulated and solved with preliminary validation applied to a 1D Engine model followed by implementation on an experimental rapid prototyping control system. The MPC based control demonstrates the ability to co-ordinate different engine and air-path actuators simultaneously for torque-tracking with minimal constraint violation. Avenues for further improvement have been identified and discussed

Flexible and robust control of heavy duty diesel engine airpath using data driven disturbance observers and GPR models

Diesel engine airpath control is crucial for modern engine development due to increasingly stringent emission regulations. This thesis aims to develop and validate a exible and robust control approach to this problem for speci cally heavy-duty engines. It focuses on estimation and control algorithms that are implementable to the current and next generation commercial electronic control units (ECU). To this end, targeting the control units in service, a data driven disturbance observer (DOB) is developed and applied for mass air ow (MAF) and manifold absolute pressure (MAP) tracking control via exhaust gas recirculation (EGR) valve and variable geometry turbine (VGT) vane. Its performance bene ts are demonstrated on the physical engine model for concept evaluation. The proposed DOB integrated with a discrete-time sliding mode controller is applied to the serial level engine control unit. Real engine performance is validated with the legal emission test cycle (WHTC - World Harmonized Transient Cycle) for heavy-duty engines and comparison with a commercially available controller is performed, and far better tracking results are obtained. Further studies are conducted in order to utilize capabilities of the next generation control units. Gaussian process regression (GPR) models are popular in automotive industry especially for emissions modeling but have not found widespread applications in airpath control yet. This thesis presents a GPR modeling of diesel engine airpath components as well as controller designs and their applications based on the developed models. Proposed GPR based feedforward and feedback controllers are validated with available physical engine models and the results have been very promisin

Decoupling control of electrified turbocharged diesel engines

Engine electrification is a critical technology in the promotion of engine fuel efficiency, among which the electrified turbocharger is regarded as a promising solution for its advantages in engine downsizing and exhaust gas energy recovery. By installing electrical devices on the turbocharger, the excess energy can be captured, stored, and re-used. The control of the energy flows in an electrified turbocharged diesel engine (ETDE) is still in its infancy. Developing a promising multi-input multi-output (MIMO) control strategy is essential in exploring the maximum benefits of electrified turbocharger. In this paper, the dynamics in an ETDE, especially the couplings among multiple loops in the air path are analyzed. Based on the analysis, a model-based MIMO decoupling control framework is designed to regulate the air path dynamics. The proposed control strategy can achieve fast and accurate tracking on selected control variables and is successfully validated on a physical model in simulations

A STUDY OF MODEL-BASED CONTROL STRATEGY FOR A GASOLINE TURBOCHARGED DIRECT INJECTION SPARK IGNITED ENGINE

To meet increasingly stringent fuel economy and emissions legislation, more advanced technologies have been added to spark-ignition (SI) engines, thus exponentially increase the complexity and calibration work of traditional map-based engine control. To achieve better engine performance without introducing significant calibration efforts and make the developed control system easily adapt to future engines upgrades and designs, this research proposes a model-based optimal control system for cycle-by-cycle Gasoline Turbocharged Direct Injection (GTDI) SI engine control, which aims to deliver the requested torque output and operate the engine to achieve the best achievable fuel economy and minimum emission under wide range of engine operating conditions. This research develops a model-based ignition timing prediction strategy for combustion phasing (crank angle of fifty percent of the fuel burned, CA50) control. A control-oriented combustion model is developed to predict burn duration from ignition timing to CA50. Using the predicted burn duration, the ignition timing needed for the upcoming cycle to track optimal target CA50 is calculated by a dynamic ignition timing prediction algorithm. A Recursive-Least-Square (RLS) with Variable Forgetting Factor (VFF) based adaptation algorithm is proposed to handle operating-point-dependent model errors caused by inherent errors resulting from modeling assumptions and limited calibration points, which helps to ensure the proper performance of model-based ignition timing prediction strategy throughout the entire engine lifetime. Using the adaptive combustion model, an Adaptive Extended Kalman Filter (AEKF) based CA50 observer is developed to provide filtered CA50 estimation from cyclic variations for the closed-loop combustion phasing control. An economic nonlinear model predictive controller (E-NMPC) based GTDI SI engine control system is developed to simultaneously achieve three objectives: tracking the requested net indicated mean effective pressure (IMEPn), minimizing the SFC, and reducing NOx emissions. The developed E-NMPC engine control system can achieve the above objectives by controlling throttle position, IVC timing, CA50, exhaust valve opening (EVO) timing, and wastegate position at the same time without violating engine operating constraints. A control-oriented engine model is developed and integrated into the E-NMPC to predict future engine behaviors. A high-fidelity 1-D GT-POWER engine model is developed and used as the plant model to tune and validate the developed control system. The performance of the entire model-based engine control system is examined through the software-in-the-loop (SIL) simulation using on-road vehicle test data

Optimal air and fuel-path control of a diesel engine

The work reported in this thesis explores innovative control structures and controller design for a heavy duty Caterpillar C6.6 diesel engine. The aim of the work is not only to demonstrate the optimisation of engine performance in terms of fuel consumption, NOx and soot emissions, but also to explore ways to reduce lengthy calibration time and its associated high costs. The test engine is equipped with high pressure exhaust gas recirculation (EGR) and a variable geometry turbocharger (VGT). Consequently, there are two principal inputs in the air-path: EGR valve position and VGT vane position. The fuel injection system is common rail, with injectors electrically actuated and includes a multi-pulse injection mode. With two-pulse injection mode, there are as many as five control variables in the fuel-path needing to be adjusted for different engine operating conditions. [Continues.