Jakob Andert

Decoupling of consecutive gasoline controlled auto-ignition combustion cycles by field programmable gate array based real-time cylinder pressure analysis

Gasoline controlled auto-ignition combustion offers high potential for CO2 emission reduction, but faces challenges regarding combustion stability and high sensitivity to changing boundary conditions. Combustion chamber recirculation allows a wide operation range, but results in a strong coupling of consecutive cycles due to residuals that are transferred to the subsequent combustion cycle. The cycle coupling leads to phases of unstable operation with reduced efficiency and increased emission levels. State-of-the-art control algorithms use data-driven models of gasoline controlled auto-ignition combustion to achieve cycle-to-cycle control of the process or use offline calibration and optimization. A closed-loop control is proposed and implemented on a rapid control prototyping engine control unit. The control algorithm continuously calculates the current residual fuel in the combustion chamber. The heat release is observed and compared with the theoretical heat release of the injected fuel mass. The rate of unburned fuel mass transferred to the subsequent cycle is calculated offline by a detailed gas exchange model. Based on this information, the control algorithm adapts the injected fuel quantity for each cycle individually using an inverse injector model. In this article, a concept for decoupling consecutive cycles is presented to reduce the deviations of the indicated mean effective pressure and thus the heat release. Unstable sequences are analyzed in the time domain, and unburned residuals are identified as a strong correlating factor for consecutive cycles. Using real-time cylinder pressure analysis based on a field programmable gate array enables the online calculation of unburned residual fuel. Based on this calculation, the injection of each cycle can be adapted individually to decouple consecutive cycles and avoid unstable operation. The results of the control algorithm and the stabilization of the gasoline controlled auto-ignition combustion are validated using a single-cylinder research engine and compared to steady-state operation.

Model Based Control of Gasoline Controlled Auto Ignition

Innovative low-temperature combustion modes for internal combustion engines, such as gasoline-controlled auto-ignition, impose very high requirements on the process control. On one hand, fast reference tracking for the engine load and the combustion phasing is needed, while at the same time, numerous disturbances acting on the highly sensitive process have to be rejected in order to guarantee stable operation at a wide operating range. Model-based predictive control concepts have a great potential to fulfill these requirements. In this contribution, a model-based predictive control consisting of a stationary and dynamic optimization stage is introduced. It is able to account for the characteristic cycle-to-cycle dynamics which occur in gasoline-controlled auto-ignition and also handle constraints imposed on the manipulated and controlled variables of the process.

NVH Optimization of Range Extender Engines by Electric Torque Profile Shaping

Range extender operation in an electric vehicle should be imperceptible to the driver from a noise/vibration standpoint. Rolling torque compensation allows virtually vibration-free range extender engine operation by utilizing a balanced counter-rotating inertia that is geared to the cranktrain. The combustion process results in engine torque fluctuations that could cause gear rattle in such a system due to a combination of torque reversal and lash in the geared connection. This brief paper addresses the problem of gear rattle in a rolling torque compensation system. First, a preloaded split gear is introduced as a potential mechanical solution to eliminate the clearance in the gear contact zone. In addition, an approach for a mechatronic solution involving active shaping of the generator torque is introduced. This methodology includes measurement of the combustion engine torque via cylinder pressure indication data, calculation of allowable torque limits, and the determination of a generator torque profile to address gear rattle. A multicriteria cost function is introduced to determine the optimal torque within the established constraints. Variations of the cost function are investigated with respect to their impact on efficiency and range extender acoustics.

Reduced Order Modeling for Multi-scale Control of Low Temperature Combustion Engines

Internal combustion engines face tightening limits on pollutant and greenhouse gas emissions. Therefore, new solutions for clean combustion have to be found. Low Temperature Combustion is a promising technology in this regard, as it is able to reduce pollutant emissions while increasing the engine’s efficiency. Recent research has shown that closed-loop control manages to stabilize the process. Nevertheless, sensitivity to varying boundary conditions and a narrow operating range remain unfavorable. To investigate new control concepts such as in-cycle feedback, computationally feasible cycle-resolved models become necessary. This work presents a low order model for Gasoline Controlled Auto Ignition (GCAI) that is continuous in time and computes the pressure trace over the entire combustion cycle. A comparison between simulation and measurement supports the suitability of the modeling approach. Furthermore, the model captures the characteristic transition of system dynamics in case GCAI during late combustion.

Influence of sensor and communication setup on electric cam phaser control quality

This study investigates the control quality of an electric cam phaser system. The impact of different sensor concepts, synchronization algorithms, controller and hardware topologies on the control quality is examined by using a transient simulation covering the electric cam phaser, valve train, mechanical transmission and a wide variety of cam- and crankshaft trigger wheels. Limited angular accuracy effects are simulated by realistic sensor models and the processing of sensor signals by a real-time capable synchronization algorithm. Nonlinear friction in transmission and valve train are considered by the simulation accordingly. Furthermore, the effects of distributed controller algorithms based on conventional electronic control units are evaluated. Communication latencies have a strong impact on the control plant and are taken into account during controller definition. The effects of different layouts are compared in the time domain, and a sensitivity analysis is carried out to evaluate the effects of different parameters on the cam phasing control quality. The control quality is measured in terms of overshoot, phasing duration and energy consumption of a phasing event. Using a sensor fusion for the current cam phasing angle and an integrated controller layout – that is, an architecture without any communication delay – improves the controllability and reduces overshooting, phasing duration and electrical energy consumption under transient conditions.

A simulation-based case study for powertrain efficiency improvement by automated driving functions

An increasing level of driving automation and a successive electrification of modern powertrains enable a higher degree of freedom to improve vehicle fuel efficiency and reduce pollutant emissions. Currently, both domains themselves, driving automation as well as powertrain electrification, face the challenge of a rising development complexity with extensive use of virtual testing environments. However, state-of-the-art virtual testing environments typically strictly focus on just one domain and neglect the other. This paper shows the results of a simulation-based case study considering both domains simultaneously. The influence of energy saving automated functionalities on a conventional, a hybrid, and a pure electric powertrain is investigated for a carefully selected inner-city driving scenario. The vehicle simulation models for the different powertrain configurations are calibrated using test bench results and vehicle measurements. A model predictive acceleration controller is developed for realizing the speed optimization function. By considering traffic conditions such as traffic light schedules and a preceding vehicle as the boundary conditions, unnecessary accelerations and decelerations are avoided to reduce the energy demand. The case study is realized by applying this function to the three powertrains variants. As a final result, a clear difference in energy demand is observed: the hybrid powertrain benefits the most in terms of energy demand reduction in the given use case. The results clearly underscore that in future vehicle development programs, the powertrain and the real-world driving functionalities have to be optimized simultaneously to minimize the energy demand during everyday vehicle operation.

X-in-the-Loop-basierte Kalibrierung: HiL Simulation eines virtuellen Dieselantriebsstrangs

The efforts to improve the performances and reduce pollutant emissions of passenger car diesel powertrains have led to technological evolutions on both engine and exhaust aftertreatment sides. The multitude of different technologies has increased the system complexity. Stable control and robust monitoring of the Engine Control Unit (ECU) become mandatory.

Autoregressive modeling of cycle-to-cycle correlations in homogeneous charge compression ignition combustion

Homogeneous charge compression ignition or gasoline controlled auto-ignition combustion is characterized by a strong coupling of consecutive cycles, which is caused by residuals from the predecessor cycle. Closed-loop combustion control is considered a promising technology to actively stabilize the process. Model-based control algorithms require precise prediction models that are calculated in real time. In this article, a new approach for the transient measurement of the auto-ignition process and the data-driven modeling of combustion phasing and load is presented. Gasoline controlled auto-ignition combustion is modeled as an autoregressive process to represent the cycle-to-cycle coupling effects. The process order was estimated by partial autocorrelation analysis of steady-state operation measurements. No significant correlations are found for lags that are greater than one. This observation is consistent with the assumption that cycle coupling is mainly caused by the amount of exhaust gas that is directly transferred to the consecutive combustion. Because steady-state operation results in a hard coupling of actuation and feedback variables, only minor variations of the test data can be achieved. The steady-state tests delivered insufficient data for the generalized modeling of the transient autoregressive effects. A new transient testing and measurement approach is required, which maximizes the variation of the predecessor cycle’s characteristics. Dynamic measurements were performed with the individual actuation of the injection strategy for each combustion cycle. A polynomial model is proposed to predict the combustion phasing and load. The regression analysis shows no overfitting for higher polynomial orders; nevertheless, a first-order polynomial was selected because of the good extrapolation capabilities of extreme outliers. The prediction algorithm was implemented in MATLAB/Simulink and transferred to a real-time-capable engine control unit. The verification of the approach was performed by test bench measurements in dynamic operation. The combustion phasing was precisely predicted using the autoregressive model. The combustion phasing prediction error could be reduced by 53% in comparison to a state-of-the-art mean value-based prediction. This work provides the basis for the development of a closed-loop autoregressive model-based control for gasoline controlled auto-ignition combustion.

Development and experimental validation of a real-time capable field programmable gate array–based gas exchange model for negative valve overlap:

Homogeneous charge compression ignition has the potential to significantly reduce NO x emissions, while maintaining a high fuel efficiency. Homogeneous charge compression ignition is characterized by compression-induced autoignition of a lean homogeneous air–fuel mixture. Combustion timing is highly dependent on the in-cylinder state including pressure, temperature and trapped mass. To control homogeneous charge compression ignition combustion, it is necessary to have an accurate representation of the gas exchange process. Currently, microprocessor-based engine control units require that the gas exchange process is linearized around a desired operating point to simplify the model for real-time implementation. This reduces the models’ ability to handle disturbances and limits the flexibility of the model. However, using a field programmable gate array, a detailed simulation of the physical gas exchange process can be implemented in real time. This paper outlines the process of converting physical governing equations to an offline zero-dimensional gas exchange model. The process used to convert this model to a field programmable gate array capable model is described. This model is experimentally validated using a single cylinder research engine with electromagnetic valves to record real-time field programmable gate array gas exchange results and comparing to the offline zero-dimensional physical model. The field programmable gate array model is able to accurately calculate the cylinder temperature and cylinder mass at 0.1 °CA intervals during the gas exchange process for a range of negative valve overlaps, boost conditions and engine speeds making the model useful for future real-time control applications.

Road-to-rig-to-desktop: Virtual development using real-time engine modelling and powertrain co-simulation

By front-loading of the conventional vehicle testing to engine test bench or even further forward to offline simulations, it is possible to assess a large variation of powertrain design parameters and testing manoeuvres in the early development stages. This entails a substantial cost reduction compared to physical vehicle testing and hence an optimisation of the modern powertrain development process. This approach is often referred to as road-to-rig-to-desktop. To demonstrate the potential of this road-to-rig-to-desktop methodology as a seamless development process, a crank angle–resolved real-time engine model for a turbocharged gasoline engine was built with the simulation tool GT-POWER®. The model was validated with measurement data from an engine test bench and integrated into a vehicle co-simulation, which also includes a dual clutch transmission, the chassis, the environment and the automated driver. The most relevant functions of the engine and the transmission control systems were implemented in a Simulink-based software control unit. To verify the engine model in the transient vehicle simulation, two 900-s time windows from a 2-h real driving emission test, representing urban and motorway conditions, are simulated using the developed co-simulation platform. The simulation results are compared with the respective vehicle measurement data. The fuel consumption deviation caused by the combustion engine model is within 5%. The transient system behaviour and the dominant engine operation points could be predicted with a satisfying accuracy.