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Virtual test drive generates realistic fuel consumption results

Virtual test drive generates realistic fuel consumption results

Technology News |
By eeNews Europe



The standard fuel consumption measurement method utilizes the New European Driving Cycle (NEDC), but this method increasingly is criticized for its susceptibility to optimizations that render the results irrelevant for normal every day use. Therefore, legislators will prescribe future measurements to be made in realistic real-world operation. Emission measurements in real-world operation are already required by the EURO 6 standard for trucks. This procedure is currently in preparation for passenger cars as well and will revolutionize the standardized measuring methods. In view of an increasing number of variants the early validation of modern drive concepts poses further challenges. The combination of innovative test rig technology and powerful simulation tools can provide answers to these issues.

The open integration and test platform CarMaker by IPG Automotive allows the consistent shifting of real-world test tracks into simulation and onto test rigs (e.g. AVL engine and powertrain test rigs). Virtual 3D roads are imported either as digital map data (e.g. from NAVTEQ, Bing or Google Earth) or as test and race track data obtained from real-world measurements. Any desired customer road or track can thus be used for the measurements in real-world operation on the test rig. Virtual vehicle prototypes with various drivers can be dispatched for virtual test driving on these 3D roads. As the driver models are capable of using different, consumption-relevant driving styles – from sporty to fuel-saving – they model the wide range of real-world customer behavior. During the test drive the virtual drivers respond to various traffic scenarios much as human drivers would in real traffic or comply with maneuver instructions. They range from driving up a steep hill from rest, sudden braking while cornering through to challenging tasks through the interaction with driver assistance systems in stop-and-go situations, for example.

The test results thereby obtained can be reproduced and compared at any time as the test conditions can be exactly repeated. This makes it possible, for instance, to analyze and optimize the actual fuel consumption and emission performance of a new vehicle type or drive concept. A large number of vehicle variants can be validated this way. The efficiency of the operating strategies of a hybrid electric vehicle or the range of a full electric vehicle can be determined at an early stage as well. This provides a safeguard against subsequent surprises and assists development engineers in finding the best compromise between dynamics and efficiency.

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