Kaiserstr. 10; Karlsruhe, Germany *corresponding Author

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1 Applied Mechanics and Materials Online: ISSN: , Vol. 391, pp doi: / Trans Tech Publications, Switzerland Time Efficient Testing of Hybrid Electric Vehicles using Automated Identificated Physical Model Structures Albert Albers a, Alexander Schwarz b,*, Rolf Hettel c, and Matthias Behrendt d 1 Karlsruher Institut für Technologie (KIT);IPEK Institut für Produktentwicklung; Campus Süd; Kaiserstr. 10; Karlsruhe, Germany *corresponding Author a Albert.Albers@kit.edu, b Alexander.Schwarz@kit.edu, c Matthias.Behrendt@kit.edu, d Rolf.Hettel@kit.edu Keywords: hybrid testing; test-based optimization; time-efficient; DOE; model-based, model identification, X-in-the-Loop Abstract. Validation and optimization of technical systems are central activities in the product development process. One part of it is the calibration and validation on a level, which covers the whole vehicle. The aspect, that plays the most important role in both validation and optimization, is the driving condition. Especially in the case of hybrid vehicles, state variables like the state of charge (SOC) have great influence on the operating strategy and therefore on assessment criteria. The article s objective is to present a procedure, which performs the conditioning and brings the planned maneuver into an order, which reduces the total needed conditioning duration. Thereby a lot of time can be saved, according to the type and amount of the possible maneuver and state values. In addition to optimizing the order of conventional maneuver, the procedure can be used to optimize the list of maneuver in a DOE-Plan. Thereby the maneuver of the individual criteria can be re-sorted as well as the designparametervariation. The IPEK-X-in-the-Loop framework (XiL) is the basis for the approach and will be used as a validation environment in an acoustic roller test bench with vehicle-in-the-loop technology. Process For re-sorting the maneuver, a model of the vehicle is needed, which is able to calculate the necessary conditioning time between the maneuver. Since only the relative conditioning times are essential, this model can be simple for the purpose of re-sorting. Important in this context is the relative time of the condition phases. But the higher the model s accuracy, the more accurately the total time will be estimated. Among other things, this quantity is important for planning the availability of the test bench. Besides the conventional modeling methods, also models, which are parameterized with the help of test data, can be used. The following alternatives can be used to obtain the necessary test data: testdata from other measurements In the ideal case, data from other tests are available, which can be used for the identification. testdata from parts of the planned tests. When some of the maneuver have got the same initial and end states, these can be performed in advance, because re-sorting can t achieve a reduction of time. These test data can be used to identify the model and then re-sort the remaining maneuver. identification maneuver Alternatively to the first two possibilities, test data for modeling can be identified, too. In this case we need to examine, if the expenditure of time for the identification tests is even less than the time saving. Another way to calculate the optimal order is to use an initial model, which will be parameterized continuously during the tests. Thereby, the tests, that were already performed, are used to improve the model and to calculate the best sequence of the remaining maneuver. All rights reserved. No part of contents of this paper may be reproduced or transmitted in any form or by any means without the written permission of Trans Tech Publications, (ID: , Pennsylvania State University, University Park, USA-05/03/16,06:01:07)

2 Applied Mechanics and Materials Vol For the example vehicle, accelerations with constant accelerator pedal position (10% steps) and subsequent decelerations are used for the identification maneuver (see figure 1). XiL- validation environment Fig.1. Identification maneuver The vehicle-in-the-loop-layer of the XiL- Framework [1 ] [2 ] is used to perform the tests. The X indicates the unit-under-test (uut), which will be completed to a whole vehicle with the suitable simulation, interacting with the driver and the environment. The components can either be real ones like the test bench, software models, or combinations of both of them. Thereby, also singular components can be assessed and optimized on an overall vehicle level. For this examination, the vehicle-in-the-loop layer is used. This means, that a real vehicle exists on the roller test bench, and influences like traffic, slope and wind are simulated additionally. This way real tracks can be reproduced on the test bench. Fig. 2. IPEK X-in-the-Loop-Framework [1 ] [2 ] For the actuation of the vehicle in the conditioning phases, a virtual driver is used. The model of the virtual driver is executed on a real-time computer, which gets the relevant values from the vehicle s CAN-Bus (velocity, gear, SOC, speeds of rotation,..)

3 120 Technologies of Mechanical Engineering Industry Identification Fig. 3. Example vehicle in validation environment The test data from the identification maneuver are used to collect the parameters of a relatively simple vehicle model (see figure 4). For that, fundamentally different optimization algorithms can be used for identifying the parameters. In this article a generic optimization algorithm was used. The aim of the optimizer is, that the model will behave like the unit-under-test (here: vehicle). The relative weight of the medial relative deviation of the different state variables is used as an evaluation parameter for the algorithm (see equation 1). (1) Verification Fig. 4. Model structure To verify the model, the test data is simulated with identificated model. Then the deviation of the state variables is evaluated. Figure 5 shows an exemplary result.

4 Applied Mechanics and Materials Vol Optimization Fig. 5. Exemplary result for one simple modelstructure After that the model is built and the test data are verified, the model can be used to calculate the final states of the singular maneuver. Afterwards, the conditioning phases between all maneuver are calculated on the basis of the model. This means, that - for each maneuver - the relevant time is calculated, for taking the system from the final states of a maneuver to the remaining maneuver. These results are then filed as a table, such as figure 1. Fig. 6. Table for conditioning times This table forms the basis for a combinatorial optimization of the type travelling salesman, each maneuver needs to be performed one time. The order, causing the shortest total duration of conditioning phases, is sought. For the optimization itself, different combinatorial optimization algorithm can be applied (see [5]). For a small amount of tests, all possibilities can be calculated, too (complete enumeration). By this, the absolute optimum can be calculated exactly. However, the computing time increases drastically (factorial) with the number of tests. From an amount of nine maneuver upwards, this procedure cannot be recommended anymore, and therefore combinatorial optimizers are applied. Although these will not necessarily reach the optimum, they will never be worse than the initial order and they cause considerably less computing time. In this case, a MST-heuristic is used for the combinatorial optimization. Conclusion and Outlook This article presents a procedure, allowing us to optimize conventional test runs and DOE-testing-plans, and execute them reproducibly on the roller test bench. The amount of time saved depends on the sort and the amount of maneuver.

5 122 Technologies of Mechanical Engineering Industry The next step is to conduct this method to several new development tasks to quantify the statistical improvement. For the evaluation of the shifting quality of a vehicle with a 7-speed-douple-clutch transmission, a time-saving of 80 % compared to a test driver on the test track can be achieved (see [5]). References [1] Albers, A., Düser, T. (2009). Integration von Simulation und Test am Beispiel Vehicle-in-the-loop auf dem Rollenprüfstand und im Fahrversuch [2] Albers, A., Behrendt, & Ott, S. (2010). Validation-Central Activity to Ensure Individual Mobility. [3] Albers, A., Lerspalungsanti, S., Düser, T., & Ott, S.(2009). Design Parameter Investigation in Customer-oriented Drive Train Development Using Human Senation Modeling Tools. [4] Albers, A., Alexander Schwarz, Matthias Behrendt, & Rolf Hettel. (2012). Time-efficient method fortest-based optimization of technical systems using physical models. In ASME 2012 International Mechanical Engineering Congress & Exposition. SAE [5] Albers A., Schwarz A., Hettel R., Behrendt M Method for the time-saving capturing of characteristic Gear shifting Diagrams of vehicles on the Rollertest Bench carried out with dual clutch transmissions 6th International CTI Symposium and Exhibition North America

6 Technologies of Mechanical Engineering Industry / Time Efficient Testing of Hybrid Electric Vehicles Using Automated Identificated Physical Model Structures /