Testing with Virtual Prototype Vehicles on the Test Bench

© IPG Automotive

AUTHORS

Dipl.-Ing. Christian Lensch-Franzen

is Head of Engineering at APL Automobil-Prüftechnik Landau

GmbH in Landau (Germany).

Dipl.-Ing. Michael Friedmann is Project Engineer in the Basic

Development/Research Team in the Engineering Department at APL Automobil-Prüftechnik Landau

GmbH in Landau (Germany).

Dr.-Ing. Christian Donn is Manager Business

Development at IPG Automotive in Karlsruhe (Germany).

Dipl.-Ing. Christian Rohrpasser is Engineer for Test Systems and

Engineering at IPG Automotive in Karlsruhe (Germany).

Real Driving Emissions

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DEVELOPMENT REAL DRIvInG EMISSIOnS

REPRODUCIBLE POWERTRAIN DEVELOPMENT THROUGH VIRTUALISATION

Pollutant emission and fuel consumption of vehicles under real on-road driving conditions are increasingly becoming the focus of public and legislative attention. The challenge lies in the development of robust vehicle propulsion systems which ensure adherence to emission limit val-ues and the manufacturers’ specifica-tions throughout the vehicles’ lifetime, in addition to the requested driving dynamics, drivability and durability. A variety of influencing factors and growing system requirements necessitate advanced methods for propulsion system development in order to facilitate the robust design and calibration of the

entire system across the complete range of use in terms of emissions, FIGURE 1 [1, 2].

The quantification of the influence of individual measures or changes to the propulsion system plays a key role in the development process – for example inter-nal engine modifications, electrification or exhaust gas aftertreatment systems on the hardware level, as well as calibration variants with regard to a parameterisa-tion and operating strategy that is opti-mal for RDE on the software level. The evaluation and specific development of technically optimal measures for differ-ent vehicle concepts require representa-tive real driving conditions in addition to the reproducibility and robustness of tests. Due to a range of influences that are external and dependent on the pro-

cess, there is no such reproducibility in on-road testing. The emission compari-son of one single module of the same, five times driven RDE cycle shows despite subjectively comparable driving style and similar traffic conditions a var-iance of 11 % in the cumulated normal-ised particle emission. Tests on the test bench, in contrast, have proved to achieve a high reproducibility as well as a high level of automation, which is shown in the smaller variance of 4 %, FIGURE 2. Therefore, the objective is to transfer representative real driving flexi-bly and precisely to test benches, thereby enabling system development in a repro-ducible environment.

DEVELOPMENT PROCESS METHODOLOGY

On the test benches of APL, real driving is transferred into the test environment in a way that is test-specific and optimally adapted to the requirements. Analogous to the test matrix in FIGURE 3, there is a distinction between the type of test bench and the level of complexity of the sub-systems to be tested.

For this purpose, a multidimensional testing matrix is generated which com-prises either purely simulative studies in the office, component test benches,

With virtual vehicle prototypes and the integration

of real driving simulation on test benches, new paths

can be explored in propulsion system development.

In cooperation with IPG Automotive, APL widens

the scope of approaches to the development of

RDE-optimised propulsion systems.

Real Driving Emissions

FIGURE 1 Use of simulation along the development process chain under RDE boundary conditions (© APL)

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endurance testing of systems, complex engine test benches, holistic powertrain testing or the examination of the whole vehicle on the chassis dynamometer or on the real road. In the field of endur-ance testing which aims at ensuring the operational stability using adequate means, the target course and load spec-trum can be specified as rotational speedaccelerator pedal value sequences in the simplest case. In the case of a specified vehicle speed curve, at least a simple longitudinal dynamics model needs to be used and parameterised cor-respondingly. For the reproducible mod-elling of driving cycles that are less dynamic and required by law, such as the NEDC, this may be an effective and cost-efficient approach.

The variants described above, how-ever, have the disadvantage that essen-tial aspects which influence emissions

such as traffic flow or driver behaviour/style are inevitably integrated in the specified speed profile and cannot be separated according to their share in the component load or emission spectra after being recorded in the vehicle. For the robust, flexible and precise transfer of real on-road driving to test benches and for the variation of parameters and influ-encing factors, the implementation of free real driving simulation as offered by IPG Automotive’s CarMaker is indispens-able. Here, a tuneable driver model and different levels of detailing of traffic sim-ulation with reproducible stochastic traf-fic events can be used as described in the following section. Due to the seam-less use of the simulation environment in the office and on engine, powertrain and chassis dynamometers, the same models can be used for example for driver characterisation and the parame-

terisation of driving robots across plat-forms as well. APL adopts this approach in the field of complex function testing and calibration validation with a focus on system robustness, the comprehen-sion of mechanisms leading to emission genesis, the study of stochastic pheno-mena and a target-oriented parameter variation. Good modelling even allows developers adopting the approach of model-based testing to shift parameter variation to fields which are interesting for calibration purposes but for which there is no exact information from real measurement data.

The approach of real driving simula-tion is taken in the development stages illustrated in FIGURE 4, from the concep-tual phase to SOP. This ensures that the influences of vehicle properties, driver, traffic, environment boundary condi-tions and the route are considered

96.2 % 100.0 %91.3 % 89.4 % 91.3 % 93.6 % 91,1 %

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Modul 5 Fahrt 1 Modul 5 Fahrt 2 Modul 5 Fahrt 3 Modul 5 Fahrt 4 Modul 5 Fahrt 5 Mittelwert Straße Mittelwert Prüfstand

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Trip 1 – Road Trip 2 – Road Trip 3 – Road Trip 4 – Road Trip 5 – Road AV Road AV Engine test bench

FIGURE 2 Exemplary comparison of the reproducibility of measurements taken on the road and engine test bench based on the particle number (© APL)

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throughout the entire development pro-cess for the design of the hardware as well as the development of the operating strategy and calibration. Once the pro-cess chain has been completed for one product, the insights gained serve for the concept evaluation and estimation of the performance of derivatives. Derivatives of already certified powertrains can thus be tested for system robustness and criti-cal ranges can be identified early on in the development process.

REAL DRIVING SIMULATION AND ITS USE ON TEST BENCHES

The real driving simulation environment contains real-time capable models which allows for the realistic and precise mod-elling of a diverse range of vehicle types including their handling characteristics, the driver behaviour, the traffic situation and the road and its surroundings in the virtual world. With the integration on test benches, virtual test driving enables the generation of a flexible, semi-virtual RDE development environment, FIGURE 5, and thus offers a considerable potential for an increase in efficiency in propul-sion system development.

The foundation of the method for semi-virtual RDE tests presented here is the generation of virtual test tracks which are built from real routes based

on measurement or map data and which also contain traffic lights and traffic signs that are relevant for vehicle speed in addition to curves and elevation pro-files. With a vehicle model (virtual pro-totype) adapted to the real driving resistances based on the component data or vehicle coast-down curves and, if required, validated using real driving measurement data, virtual test driving is subsequently performed. The intelli-gent driver model which enables the reproducible representation of different driver types while autonomously observing traffic signs, traffic lights and the traffic plays an equally central role as the modelling of traffic conditions that are stochastic and reproducible at the same time. In addition to a deter-ministic traffic model and the optional coupling with microscopic traffic simu-lation (PTV Vissim), a phenomenologi-cal approach is available for this pur-pose which allows for the road seg-ment-specific modelling of different statistic traffic densities. Furthermore, the driver model features a function for the comparison of road and test bench tests thanks to which a measure-ment-based target speed profile can be retraced on the virtual route.

Due to the synchronised real-time coupling between real driving simula-tion and test benches, a high-perfor-

mance closed-loop integration of the real systems to be tested into the virtual environment is achieved, thereby creat-ing a semi-virtual development environ-ment, FIGURE 6. Individual subsystems such as the internal combustion engine on the test bench or the whole vehicle on chassis dynamometers can thus be integrated into the simulation environ-ment and tested in quasi-real operation. With this method, the complex model-ling of an IC engine which would be necessary for the evaluation of fuel con-sumption and emissions in transient real operation is not required in early devel-opment stages, which is an essential advantage [3].

This method allows for the precise or stochastic variation of influencing fac-tors relevant in real driving such as driver behaviour, vehicle properties and environment boundary conditions and the exact repetition of tests as required. On component test benches (for example engine, transmission or battery test benches) in contrast to test benches for the complete propulsion system or the vehicle, the remaining elements of the powertrain except the device under test are also part of the simulation environment [4] and can therefore be varied flexibly. This enables a virtual electrification of the propul-sion system or tests in different virtual

Test environment Office(MiL)

Componenttest bench

Endurancetest bench

Complex engine test bench

Powertrain test bench

Chassisdynamometer

Real driving

Driver

Environment

Vehicle

Chassis

Exhaust aftertreatment

Auxiliary units

Cooling system

Powertrain

Gearbox

Electric motor

Battery

Internal combustion engine

Simulation environment – required/constructive for powertrain development at optimal time and costs

Simulation environment – optional according to objective

Simulation environment – not effective/high degree of complexity

Hardware existent

FIGURE 3 Test matrix for the transfer of real driving into the test environment (© APL)

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proto type vehicles, which allows for the evaluation of the behaviour of the device under test in different hybrid and vehicle variants [5].

An effective use of component test benches thus becomes possible already

in early stages of the development process since it allows for fundamental decisions regarding concepts and components, without the need for real prototype vehi-cles. Throughout the course of the devel-opment process, an increasing number of

real components/assemblies can be inte-grated into the development and valida-tion process on the propulsion system test bench up to whole vehicles on chassis dynamometers. The boundary conditions and scenarios of the test, however, remain

FIGURE 5 Virtual components of the RDE development environment (© IPG Automotive)

FIGURE 4 Optimised whole vehicle development process under RDE boundary conditions (© APL)

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the same, which leads to significant sav-ings in time and cost in the overall pro-cess in addition to the good comparabil-ity of the test results. For development and application activities, real driving is thus consistently transferred from the road to the test bench, where driving can be performed with automation and inde-pendently of weather conditions or influ-ences depending on the time of day.

SUMMARY

Reproducibility of emission measure-ments cannot be attained in test driving on real roads due to a multitude of influ-ences that are external and depend on the process, while being a fundamental requirement for effective propulsion system development. Two particular strengths of tests on test benches, in contrast, are high reproducibility as well as a high level of automation. Thus, with an increasing proportion of simulation, the presented method allows to transfer representative real driving flexibly and

exactly to test benches throughout the entire development process. Based on systematic variations, the influence of vehicle-specific aspects (for example overall weight, ECU software data status, operating strategy, hardware variants), driver behaviour as well as traffic and environment boundary conditions on consumption, emissions and driving per-formance can be quantified and critical real operating conditions identified early on. As a result, with the virtualisation described, the utilisation of test benches and with it the efficiency of the propul-sion system development process can be increased significantly.

REFERENCES[1] Lensch-Franzen, C.; Gohl, M.; Mink, T.: Impact analysis of fuels, operating fluids and combustion parameters; focus raw emission behaviour. 4th Inter-national Engine Congress, Baden-Baden (Germany), 2017[2] Lensch-Franzen, C.; Gohl, M.; Becker, Mink, T.: The interaction between tribology, thermodynamics and emissions under real driving conditions (RDE). 11th International MTZ Conference The Powertrain of Tomorrow, Frankfurt/Main (Germany), 2017

[3] Disch, C.; Koch, T.; Spicher, U.; Donn, C.: Engine-in-the-Loop as a Development Tool for Emissions Optimisation in the Hybrid Context. In: MTZworldwide 75 (2014), no. 10, pp. 40-46[4] Donn, C.; Bensch, v.: Real-Time Capable Model Environment for Developing and Testing Hybrid and Battery Electric vehicles. 11th International MTZ Conference The Powertrain of Tomorrow, Frankfurt/Main (Germany), 2017[5] Donn, C.; Pfeffer, R.; Bensch, v.: Model-Based Testing on the Engine Test Bench – Semi-virtual Examination of Hybrid Powertrain Systems in Real Driving Conditions. 2017 JSAE Annual Congress, Yokohama (Japan), 2017

FIGURE 6 Virtual electrification using the example of an engine-in-the-loop test bench with different vehicle and powertrain variants (© IPG Automotive)

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