System Optimisation for the Calibration of ECU Functions
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1 DEVELOPMENT Engine Management System Optimisation for the Calibration of ECU Functions SGE The Design of Experiments method is an important tool for modeling complex systems. The transfer of models into real-time engine control units is a major challenge. A new approach to system optimisation from SGE and BRP-Rotax permits the automated calibration of engine control unit functions by optimising all calibration parameters simultaneously. 56 THE CHALLENGE OF CALIBRATION Modern development methods form the basis of projects with technical and economical success. Therefore Design of Experiments (DoE) is an important tool for modeling complex systems with the aim of increasing efficiency. However, so far this method has not provided any generally applicable answers to the question of transferring the models to realtime engine control unit (ECU) functions. These are often implemented with a variety of interdependent calibration parameters, which have to be adapted in an iterative process. The aim of calibration is to create a reliable working system under all ambient conditions over production tolerances and aging behavior. For this purpose, application-oriented, empirical methods are often used. The effort required for calibration thereby increases roughly proportionally with the number of variants and development stages as each time data is generated, evaluated and processed into calibration parameters in an identical manner. For this reason, specific software tools that are tailored to the calibration of an ECU function are developed on a regular basis. Calibration is also made more difficult because an ECU function cannot yet represent the chemical-physical correlations of an internal combustion engine in a complete and real-time manner. Thus, often only main effects are implemented so that an entirely exact setting of the calibration parameters is no longer feasible and a compromise has to be made through prioritisation. Finally another challenge
2 AUTHORS Dipl.-Ing. André Sell is Head of Methodology at SGE Ingenieur GmbH in Gräfelfing (Germany). Dipl.-Ing. (FH) Tobias Gutmann is Head of Calibration at SGE Ingenieur GmbH in Gräfelfing (Germany). Frank Gutmann, M. Eng. is Head of Software Development at SGE Ingenieur GmbH in Gräfelfing (Germany). Dipl.-Ing. Stefan Leiber is Head of Development Thermodynamics at BRP-Rotax GmbH & Co KG in Gunskirchen (Austria). FIGURE 1 Original ECU function with corresponding quality criterion (the variable and parameter names of the ECU are used in the figure) ( SGE) appears with calibration parameters whose output values cannot be determined directly or not in the entire operating range, e.g. if they cannot be measured because of knocking limits or component protection. Thus, only an indirect determination of these parameters is possible. NEW ENGINE ROTAX 915 IS Based on the proven and tested drive concept of the Rotax 912/914 engine family, BRP-Rotax is developing the new turbocharged four-cylinder engine Rotax 915 is with a charge air cooler. With 100 kw it offers more power, the best power to weight ratio in its class and a full take-off power up to at least 4600 m (15,000 ft) as well as a service ceiling of 7000 m (23,000 ft). The entire control system is designed redundantly in order to meet the high operational reliability requirements for an aircraft engine. The ECU contains two independent units (lanes), each of which can operate the entire engine independently. Therefore, all safetycritical sensors and actuators are also redundant. Since the positioning of the actuators of the two lanes is different, they require a separate base calibration some functions even require additional calibrations for different operating modes. This variety of variants, combined with the extended operating range of the aircraft engine with respect to ambient conditions, leads to an ever greater calibration effort. Therefore, this project was selected by BRP-Rotax GmbH & Co KG in cooperation with SGE Ingenieur GmbH to test and evaluate a new method for this calibration. SYSTEM OPTIMISATION A new approach of system optimisation permits the automated calibration of ECU functions by simultaneously optimising all calibration parameters. The aim is to minimise the deviation of the ECU system behavior from a reference behavior, FIGURE 1. The reference behavior describes the target state that the ECU function should map. It may be provided in the form of measured or simulated data or in the form of a databased model. The ECU function to be calibrated includes at least one, but in general, several calibration parameters, as well as one or more input and output signals in MTZ worldwide
3 DEVELOPMENT Engine Management each case. These same signals also form the interfaces of the reference system. Therefore, it is only necessary to map the inputs and outputs of the function. Information about signals within the function is not necessary, consequently the above-mentioned problem of signals which cannot be directly determined is no longer relevant. To determine the deviation between the ECU function and the reference system, the input signals of the reference system are applied to the ECU function and the resulting output signals are compared to those of the reference system. In the simplest case, the absolute differences for all the output signals are computed to a mean value that is used as a scalar quality criterion, which is then minimised by the optimisation. Since the calculation of the quality criterion is freely definable, the user has the possibility to bias the optimisation result. For example, weights can be defined depending on the operating point, the sign or the magnitude of the deviation. It is also possible to introduce empirical criteria to evaluate the calibration when it can be calculated from the input and output signals of the function. In this way, the well defined calibration of functions is, even if they cannot accurately represent the physical relations of the underlying system and thus do not permit a trivial evaluation on the basis of the deviation. The quality criterion is minimised by means of an optimisation algorithm that is simultaneously varying all the calibration parameters contained in the function. An existing initial calibration can be taken into account as the starting point of the optimisation, thus reducing the required time of the optimisation. Limitations and smoothness requirements can be considered for the calibration parameters as well. Limits are also used to achieve a reproducible result for under-determined functions. This need exists when calibration parameters are summed up or multiplied and an infinite number of combinations exist that provide the same result. IMPLEMENTATION 58 FIGURE 2 Alternative ECU function with corresponding quality criterion (the variable and parameter names of the ECU are used in the figure) ( SGE) The described method of system optimisation was implemented as an extension of the software SGE ModelArtist. This tool, which is designed for visualising, modeling and optimising complex systems, supports the use of various data formats as well as extensive calculated channels. Thus, it offers direct access to the measurement and simulation data usually without data preprocessing. Gaussian process models are then used as the basis for the optimisation algorithms. The essential components of the system optimisation are the reference system, the ECU function to be calibrated and the quality criterion. The reference system may either be represented by the loaded data or by a model. While a model is generally preferred for its positive properties regarding plausibility, the data can be accessed directly in the
4 FIGURE 3 Model volumetric efficiency for all cylinders and correlation representation for the first cylinder ( SGE) case of very large data sets that cannot be modeled. The ECU function to be calibrated is depicted in the form of a flow chart with its calibration parameters, which are set with initial values. Thus, the flow chart can be simply derived from the representation that is usually used for the ECU software development. It is also possible to use a Simu link system. The quality criterion is implemented in the same way and thus permits the described influence on the optimisation results. Before starting the optimisation, the user configures smoothness criteria and limits for the calibration parameters in the form of fixed values or depending on the form of the parameter, for example as a map. A progress bar permits a quick evaluation of the current progression of the optimisation. In addition, at any time during the optimisation there is access to interim results of the calibration parameters to be optimised, which can be viewed and stored. APPLICATION EXAMPLE For the aircraft engine Rotax 915 is, the method of system optimisation was used to calibrate the function, which determines the volumetric air efficiency of the engine individually for each cylinder depending on engine speed, ambient-to-manifold pressure ratio (PiPe_ Ratio) and ambient pressure. It was known from the previous project that this function could not accurately represent the physical relation due to an ambient pressure compensation that does not depend on the engine speed. Thus, weighting was applied to the quality criterion to prioritise high engine speeds and loads in order to increase the accuracy of the calibration in this range. The shown quality criterion of the first cylinder in FIGURE 1 was adjusted analogously to the other cylinders. In addition to the original ECU function, an alternative function was considered, that had to be evaluated. Implementing the new function is only a little effort, since only the alternative function has to be integrated into the quality criterion. The operating point dependent weighting was removed to see how the physical relations are handled, FIGURE 2. As a reference system, a Gaussian process model was trained for each cylinder using 3125 measuring points within the input range of the data, FIGURE 3. For the original function with five maps and a total of 1440 individual values to be calibrated, the optimisation needed 4 h of computing time. The result of the optimisation creates plausible maps, which could be transferred directly into the ECU after post-processing and extrapolation into non-measured areas. Examining the remaining deviations of the optimised calibration results from the measured values, TABLE 1, and the distribution of the deviations, FIGURE 4, it can clearly be see the desired effects of prioritising high engine speeds and high engine loads for the original ECU function. The alternative ECU function, shows significantly better results, as it has a more Original ECU function, original calibration Original ECU function, optimised calibration Alternative ECU function, optimised calibration Mean deviation (-38 %) (-56 %) Max. absolute deviation (-53 %) (-65 %) TABLE 1 Optimisation result overview regarding volumetric efficiency for original and alternative ECU function with original and optimised cali bration (first cylinder) ( SGE) MTZ worldwide
5 DEVELOPMENT Engine Management FIGURE 4 Optimisation result visualisation regarding volumetric efficiency for original and alternative ECU function with original and optimised calibration (first cylinder) ( SGE) SUMMARY With the presented method of system optimisation, the calibration engineer and software developer is provided with a universal tool for the automated calibration of ECU functions. The integration of the system optimisation into a tool chain of model-based calibration ensures seamless processing of measured data into optimised calibration parameters. This innovative method has been successfully applied by BRP-Rotax GmbH & Co KG in cooperation with SGE Ingenieur GmbH to optimise the base calibration of the new aircraft engine Rotax 915 is. It significantly reduced development resources and also showed the potential of further software development. even deviation distribution and smaller deviation values. The efficiency gain when using system optimisation increases disproportionately with the number of calibration variants, since the user only needs to make adjustments to the reference system and the quality criterion as well as post-processing of the calibration parameters if needed. The optimisation itself is carried out independently without the user s 60 intervention. In the present project of the aircraft engine Rotax 915 is, the necessary development resources could be more than halved to achieve the high quality requirements for the calibration regarding operational safety and fuel consumption. At the same time, potentials for a future ECU development were shown and verified by evaluating the alternative function with automated and optimised calibration. THANKS The authors would like to thank the employees of BRP-Rotax GmbH & Co KG, in particular Dr. Thomas Hametner, Director Design Engineering, Dipl. Ing. Thomas Goigitzer, Thermodynamics and Calibration Aircraft Engines, Ing. Johannes Kliemstein, Calibration Aircraft Engines, and Dipl.-Ing. Christian Sulek, Testbed and Calibration Methodology at BRP, for their support as well as Paul Schmaus, M. Eng., Calibration, SGE Ingenieur GmbH.
6 MTZ worldwide
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