Speakers Information - Controls, Measurement & Calibration Congress

Modern calibration approach for transient mixture control optimization of SI engines.

Ranjithkumar TR, Anirudh Raut, Ajay NarayanYadav, Ajay Kumar Vashisth Maruti Suzuki India Limited

ABSTRACT

Calibration of Engine Management Systems (EMS) requires considerable engineering resources during the development of modern vehicle’s powertrain integration. In view of rising system complexity and demand for shortening time to market, efficient calibration methods need to be developed. To employ a systematic and logical approach with front-loaded development, which eliminates repeated loops of EMS calibration effort, is key to modern calibration process. Such an efficient calibration approach can reduce requirement of precious resources like prototype engines, vehicles and testing facility. This paper describes an approach that helps to reduce calibration effort resulting in reduction of development time & resources by implementing modern calibration methodology. A case study of Modern Engine management calibration methodology is explained for transient mixture control optimization of SI engine.

INTRODUCTION

In an era of globalization, original equipment manufacturers (OEMs) face pressure on multiple fronts, like the need to develop a more diverse product range to strengthen market presence by developing numerous vehicle variants for new & existing products and markets. The shrinking time to market combined with rapidly increasing content and complexity of the vehicle electronics, is resulting in huge increase in calibration efforts and also challenges calibration quality.

Figure 1: Future Trend for Development time and Calibration Complexity

Engine development process focuses to optimize engine emissions and fuel consumption to meet global market requirements as well as it must provide real-time control in order to realize low fuel consumption & higher comfort. Customers have become globally mobile and EMS needs to meet expectation of meeting global quality. A robust EMS is required to achieve these targets. However, technological advancements in engine hardware and auxiliaries are necessary to meet this changing requirement which results in an increase in calibration cost, development time and various other resources. Also multiple sourcing of engine parts to cover operation risk has led to increase in complexity. In such a scenario shift from traditional application methods to modern efficient application methods is inevitable.

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Future Trend : Development Time and Calibration Complexity

Development Time Calibration Complexity

An optimized calibration refers to the data set that resides in the engine control unit (ECU) in the form of look-up tables or constants. Combined with control strategy, the optimized calibration determines the actuator positions for a given set of engine operating conditions. It must be capable of controlling the engine to meet the desired performance targets. A modern trend aimed at reducing time required for calibration, is application of statistical tools developed, where empirical models of systems are used for calibration. This new process is much more efficient than traditional techniques which rely heavily on trial-and-error optimization techniques. This paper describes calibration methodology using statistical modern approach by using HIL’s and On-desk calibration methods for various applications. Also, in order to front load the development process, it discusses the application of shifting vehicle calibration to engine bench. This paper will try to highlight the multiple ways to employ the modern calibration approach:

CALIBRATION APPROACHES:

TRADITIONAL CALIBRATION APPROACH FOR TRANSIENT MIXTURE CONTROL CALIBRATION

In most applications, calibration and algorithm development are completely independent processes. For most applications, the algorithm must be determined before the physical system has been built, which leaves less flexibility to the calibrator in developing robust calibrations. This is primarily because OEMs use standardized control algorithms for multiple platforms.

Figure 2 shows the process flow for traditional calibration approach. Traditional calibration techniques are performed widely in non-torque base EMS systems. This calibration methodology can be completed quickly and does not require the calibrator to have skill in numerical modeling and statistics.

Figure 2: Traditional Calibration Approach – Process Flow

1. Defining the desired parameters: With the help of the function frame, it is possible to identify the parameters that are best suited for altering system response in the desired manner. The desired parameters are defined by calibration engineer. The calibrator often receives a map/table structure (desired parameter). The structure dictates the input-output relationship to be calibrated and the total number of data points allowed in structure. The aim of calibration is to alter the parameters for meeting the desired output. For example during wet compensation, the output lambda gap is required to be within acceptable designed limits. 2. Grid point Selection: It is usually up to the calibration engineer to choose the grid points in the map/table structure. The calibrator will choose which points to collect data in order to capture the input-output relationship. Ideally, more refinement is chosen in complex regions and less in linear region. Effectively choosing grid points is typically completed by the calibrator’s experience. Calibration engineer should have a basic understanding of the system to be calibrated and would choose to increase refinement in certain regions and less in others, or the calibrator could choose to even space the test points into a grid. In either case, the approach lacks scientific support that performing a DoE would have and requires the calibrator to have knowledge of the system response.

3. Measure vehicle parameters and Analyze: With the help of calibration ECU, measure required engine related ECU parameters. An additional testing equipment example thermo logger, Lambda, and flow measurements were connected. Analyzing and documentation of the measured data is prepared with the help of offline tools. 4. Modify calibration parameter and measure effect changes: The parameter stored in the ECU software can be displayed as numerical value or graphs on the test PC and altered. Each time an alteration is made, system response is observed. All parameter can be altered while the engine is running so that the impacts are immediately observable and measurable. In some case the alteration were performed in offline. In the case of short-lived or transient process, it is effectively impossible to alter the parameter while the process is in progress. In such cases, the process has to be recorded during the course of a test. The measured data is saved to file and then the parameter that are to be altered are identified by analyzing the recorded data. Further tests are performed in order to evaluate the success of the adjustments made or to learn more about the process. 5. Calibration validation: Calibration confirmation is often optional in traditional calibration methods, but is critical in analyzing how the calibration will perform in regions where data was not taken and robustness of calibrated data. This helps determine the predictive nature of the map/table. The issue with validation in traditional calibration methods is that there is not a clear procedure to do if the fit does not meet expectations. If the fit meets expectations, then it is simply implemented on ECU controller. If not, a few of the options are to start over, minor adjustments between grid points or pass the calibration on with limited improvement. Hence lack systematic approach to improving the quality of the calibration. Although traditional calibration is typically effective, however in case of variants of engine HW/SW and multiple sources of engine parts traditional method becomes in-efficient as testing/validation effort need to be incurred on all the variants. In case of logic changes the change management cannot be handled efficiently by traditional method of EMS calibration. MODERN CALIBRATION APPROACH FOR TRANSIENT MIXTURE CONTROL The practice of modern calibration approach has an impact on the calibration process. Traditional methods started with measurements in the vehicle followed by the evaluation of the data for calibration. To evaluate the effect of the changed calibration further multiple iterations were necessary, where the same conditions (consider an example of engine coolant temperature, ambient temperature, etc.,) need to be reproduced. If the result of this measurement does not meet the expected quality, the loop needs to be repeated until the expected result is achieved. In this paper, 3 primary methods have been identified to employ the modern approach:

1. Modern calibration approach by using HIL:

Figure 3: Modern Calibration Approach using Hardware-in-Loop systems

2. Modern calibration approach by using On-desk calibration:

Figure 4: Modern Calibration Approach using Hardware-in-Loop systems

3. Modern calibration approach shifting vehicle function to engine bench:

Figure 5: Modern Calibration Approach using Hardware-in-Loop systems

By adopting modern calibration approach, the calibration process is changed such that time, cost and resources consumed for repeating tests in various conditions can be significantly reduced. After conducting a defined number of measurements, the data will be read and evaluated offline. The change of other calibration with regard to the relevant output signals can be directly analyzed. The final robustness check is performed under real world circumstances for final data confirmation. Hardware-in-loop systems application combined with On-desk Calibration approach: The Hardware-in-Loop (HIL) process has existed for no more than 15 to 20 years. Hardware-In-Loop is a form of real-time simulation but differs from it in the way that it is structured around a real component like an electronic control unit (ECU). HIL simulation provides an effective platform by adding the complexity of the plant under control to the test platform. All inter-connected dynamic processes of the simulated plant are mathematically represented to form the structure of the HIL system. Since in-vehicle driving tests for evaluating performance and diagnostic functionalities of Engine Management Systems are often time-consuming, expensive and not reproducible, HIL simulators allow developers to validate new hardware and software automotive solutions, respecting quality requirements and time-to-market restrictions. Figure 6: HILS Block Diagram Figure 7: Control Development V-Cycle An Engine management system development time line, software and logics (functions) undergo numerous changes in architecture to improve efficiency and reliability of the system. Every change in logic or computing architecture inevitably causes a deviation in calibration data. In traditional approach, such frequent changes will warrant repetition of time taking validation exercises. The modern calibration approach by using HIL’s setup, offer a cost-effective solution to the calibrator to alter the calibration timely without adversely affecting the development timeline.

Figure 8: Application of HILS combined with On-desk calibration approach

1. Stage 1 (Bench Data) The development process moves to the vehicle calibration phase after the main engine evaluation on engine bench. Vehicle calibration phase is initiated with the receipt of the base data, which is formalized in the Bench Calibration phase. ECU data at low engine speeds and temperature compensation cannot be accurately calibrated on engine bench, owing to facility constraints (low combustion stability at low engine speeds and lack of temperature flexible engine test benches). 2. Logic Up-gradation: Software quality improvement Over the course of any EMS development timeline, software undergoes numerous changes in architecture to improve efficiency and reliability of the system. Every change in logic or computing architecture inevitably causes a deviation in calibrated data. 3. Data Generation via HILS Real time simulators (Hardware-in-loop systems) can be utilized to evaluate the effect of EMS software change. HIL systems offer real time simulations for multiple iterations, in various testing condition. This greatly accelerates the incorporation of software changes in the final ECU data. 4. Data Optimization via On-Desk Tool The data generated by the real time simulator helps to identify the focus area for calibration. In the modern calibration approach, data optimization is performed using a combination of statistical tools and empirical models. An application of an on-desk tool can be illustrated in the following case study: 5. Data Validation on Vehicle Despite the use of on-desk calibration tools, final validation is required on vehicle to mitigate the risk of erroneous HILS model. It results in confirming the robustness of calibration achieved. Vehicle response to calibrated data is evaluated at this stage and robustness of calibration solution is judged. 6. Check Effect of Logic change on related functions Over the course of the development process, the software undergoes numerous upgrades. These upgrades are necessary for improving the accuracy of the mathematical models being employed. At this stage, the nature of change and its effect on the calibrated data is checked. In case the change influences the data, on-desk tools are used to determine the effect of the logic change and mathematically alter the software data. The data is optimized to level the calibration quality with original software version. 7. Data Validation on Vehicle After the software has been formalized, and data has been optimized, the calibrated data is validated on the actual vehicle. This serves as a final evaluation stage and checks the robustness of the optimized data.

Case Study (i) - Application of base temp compensation and Warm-up Injection Loss calibration by using HIL setup:

Background: During the development of a particular new product, numerous software editions are released. In the edition under question, the air temperature compensation determination logic was improved. The modified software version used Intake Port temperature model to correct the density of the intake charge. In the previous versions, air temperature compensation was calculated based on Intake Air Temperature sensor. Due to above reason related functions and calibration areas were identified that would be affected by this above logic change. One such function identified for re-calibration was the Engine warm-up injection loss compensation function.

Engine warm-up compensation function depends on the following variables: 1. Engine Coolant temperature 2. Engine Speed and Engine load (Air charge ratio) Old Logic has been illustrated as below:

Figure 9: Old Air Charge Estimation Logic (without Port Model Temperature Logic) New Logic considering Port Model Temperature has been illustrated below:

Figure 10: New Air Charge Estimation Logic (with Port Model Temperature Logic) Due to above logic change, the load dependent loss compensation needs to be adjusted. To compensate the loss of fuel during engine cold to warm-up situation this loss compensation is applied. As the fuel supplied to combustion chamber cannot contribute to the combustion completely.

Air charge temperature compensation by considering Intake Air Temperature.

Air charge temperature compensation by considering Intake port model temperature.

Air charge estimation MAP

Air charge estimation MAP

In a traditional approach, the calibrator would have to collect data to cover the range of the controlling variables i.e. across the engine load - engine speed MAP and for coolant temperatures. Considering constraints for facility and vehicle soaking times, this would prove counter-productive considering the time, cost and manpower involved. In this particular situation, modern calibration approach was used to collect, analyze and calibrate the warm-up function. HIL’s calibration approaches explained below in steps. Step 1: After the base warm-up data calibration (coolant temperature base), warm-up gain compensation was confirmed for modified software version. A hardware-in-loop system was used for real-time simulation of the test in various temperature conditions. Air charge data was collected for both software versions. Step 2: Data was analyzed to determine the deviation in the charge estimation from reference data generated from software version 1. The charge gap ratio is a measure of the offset in the estimated air charge entering the cylinder. This has to be taken into account during Engine warm-up calibration. The desired warm-up correction due to deviation in charge estimation, after software change has been illustrated below: Figure 11: Desired Warm-up behavior at 1200 rpm Figure 12: Desired Warm-up behavior at 2400 rpm Figure 13: Desired Warm-up Behavior at 4000 rpm Figure 14: Final warm-up loss (Load compensation) Step 3: Charge Gap Ratio thus determined is considered to be the target deviation in loss of injection (warm-up loss). During the calibration of Engine Warm-up Map (Engine Load – Engine Speed), data can be optimized to meet desired injection loss deviation. This process can be automated using statistical and empirical tools to optimize data for different engine speeds.

Figure 15: Charge Gap Ratio deviation Original Step 4: After the completion of data optimization, the calibrated data needs to be evaluated on actual vehicle / cold engine test bench. This serves as the final validation before fix ECU data.

Figure 16: Load dependent Warm-up Loss compensation On-Desk Calibration methods like statistical and empirical methods: On-Desk Calibration methods are performed with the help of statistical and empirical tools. As has been discussed in the previous section, the rising demand for shorter time to market and increase in content and complexity of the EMS, traditional methods are making way for modern calibration methods. Empirical, statistical and poly curve fitting method serve as effective tools for the On-Desk calibration process. This will lead to reduction in development time, cost and man-hours spent. Similar to the traditional calibration approach, on-desk calibration is also an iterative process but the iterations are fewer in number and have a shorter lead time. The dynamic mixture correction which is necessary to compensate for the load changes due to throttle valve movements is provided by the transition compensation. This facility is required in order to achieve best-possible driveability and exhaust gas behavior. The basic process flow for the On-desk approach has been summarized below

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Figure 17: Application of On-desk tools: Process Flow

1. Data Collection on Actual Vehicle / Bench Base data can be collected on the Engine Bench or real vehicle. As discussed in the previous section, HIL setup can also be utilized to collect data. 2. Use of On-desk tool for Calibration: The data generated by the real time simulator helps to identify the focus area for calibration. In the modern calibration approach, data optimization is performed using a combination of statistical tools and empirical models. An application for the On-desk approach was developed and utilized for calibrating Injection Wet Loss compensation during transient operation. This has been discussed in Case Study (ii). 3. Run Simulation for calibrated data Using the On-desk tool, various iterations can be simulated on-desk. It allows the calibrator to accurately optimize the data. Evaluating the calibration quality at this stage will ensure an error-free validation. 4. Validate the simulated data on vehicle / bench After the software has been formalized, and data has been optimized, the calibrated data is validated on the actual vehicle. This serves as a final evaluation stage and checks the robustness of the optimized data Case Study (ii): Injection Wet (Transient fueling) calibration by using on-desk tools: With manifold injection, the fuel’s tendency to evaporate depends to a large extent upon the manifold pressure. This leads to the development of fuel wall film on the intake manifold in the vicinity of the intake valves. Sudden changes in engine load, as occur when the throttle-valve opening changes suddenly, lead to changes in this wall film. Heavy acceleration causes the intake-manifold pressure to increase so that the fuel’s evaporation tendency deteriorates, and wall film thickens as a result. Being as a portion of the fuel has been deposited to form the wall film, the A/F mixture leans off temporarily until the wall film has stabilized. Similarly, sudden deceleration leads to enrichment of the A/F mixture since the drop in manifold pressure causes a reduction in the wall film and the fuel from the wall film is drawn into the cylinder. A temperature dependent correction function (Wet compensation) is used to correct the A/F mixture so as to ensure not only the best possible drivability, but also the constant A/F ratio as needed for the catalytic converter. Wall fi lm effects are also encountered at the cylinder walls. Transient calibration on-desk calculation tool was used to calibrate the injection wet amount. The main requirement of transient compensation is to minimize lambda deviation during sudden acceleration and de-acceleration condition. To model an Injection wet amount on desk calibration tools was made based on reverse wet model. The reverse wet model gives an output of simulated lambda based on calculated fuel injection amount. Based on the logics, function and the reverse model, offline calibration tool was made with the help of statistical and empirical method. For example during transient calibration statistical method was used to calibrate the injection wet and vapor compensation ratio.

Figure 18: Graph created by On-Desk Tool

Figure 19: Effect of on-desk approach on calibration efficiency

For the transient calibration data acquisition was done on the flexible temperature engine bench. Wet ratio and vapor time constant are the two important parameters used to calibrate injection wet amount (transient fueling). Predicated air flow rate and base injection fuel amount were determined from the measured data. With the help of calibration tool, wet ratio and vapor time constants are calibrated. The calibrated data is simulated offline and lambda deviation is checked. If the lambda deviation is more than a set threshold limit, wet ratio and vapor time constant needs to be adjusted and iteration is repeated again in offline tool. Data is fixed once the lambda deviation is within acceptable limits. The fixed calibrated data needs to be re-validated on actual vehicle to confirm the actual vehicle performance. In case lambda deviation exceeds the specified threshold, minor adjustments can be made using the on-desk approach.

Shift vehicle calibration activity to Engine Bench

As discussed in the previous sections, combination of HIL setup and On-desk tools has helped to minimize test duration. In the case studies mentioned above, final validation was performed in flexible temperature engine bench. This helped to front-load work over the course of the development and minimize soaking time for tests. Also, this helped to efficiently complete many vehicle calibrations on engine bench.

The shifting of vehicle calibration to flexible temperature engine bench provided the following benefits:

Calibration Quality improvement

Improvement in measurement repeatability

Reduction of calibration errors (due to electrical or mechanical load)

Convenient data validation process

Reduction in prototype vehicle requirement

Test duration was reduced

CONCLUSION

This paper described modern calibration approach methodologies to implement in EMS calibration development. Testing results indicate that new calibration approach followed proved to be efficient as summarized below.

Figure 20: Impact of Calibration Approach

The use of new intelligent tools will influence a tremendous amount of change in application projects. As discussed in the case studies, new tools have helped to improve facility usage by 62.5%. Consequently, it has helped to reduce the man-hours spent over the course of development by about 50%. It is imperative that the high quality standards set in place and increased complexity in engine hardware do not increase the development time and cost. Consequently, use of these intelligent tools will aid in accelerating the development process and guaranteeing a robust calibration that addresses the global customer’s requirements.

ACKNOWLEDGMENTS

This entire work would not have been possible without extensive support from Mr. Puneet Arora and Mr. Anoop Bhat and other colleagues.

REFERENCES

1. Satinder Pal Singh, “ECU calibration approach to implement improved CNG injector in existing CNG vehicles “SAE

Technical paper 2013-01-0863, doi:10.4271/2013-01-0863

2. Gasoline Management System: 2nd

Edition, Published by Robert Bosch GmbH, 2004.

3. Hardware-in-the-Loop: The Technology for testing electronic controls in Automotive engineering by Dr.Peter

Waltermann, dSPACE GmbH.

CONTACT

Ajay Kumar Vashisth Asst. General Manager – Power Train Development Division M/s Maruti Suzuki India Limited Kumar.Ajay@maruti.co.in Ranjithkumar TR Manager – Power Train Development Division M/s Maruti Suzuki India Limited Ranjithkumar.tr@maruti.co.in Anirudh Raut Asst. Manager – Power Train Development Division M/s Maruti Suzuki India Limited Anirudh.Raut@maruti.co.in Ajay Narayan Yadav Asst. Manager – Power Train Development Division M/s Maruti Suzuki India Limited AjayNarayan.Yadav@maruti.co.in

DEFINITIONS, ACRONYMS, ABBREVIATIONS

A/F Air Fuel ratio FWL Warm-up Injection Loss compensation HIL Hardware In Loop ECU Engine Control Unit EMS Engine Management System DoE Design of Experiment MDA Measure Data Analyzer