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A calibration and validation workflow will be presented in this paper, which utilizes common static global models for fuel consumption, NOx and soot. Due to the applicability for warm-up tests, e.g. New European Driving Cycle (NEDC), the models need to predict the temperature influence and will be fitted with measuring data from a conditioned engine test bed. The applied model structure consisting of a number of global data-based sub-models is configured especially for the requirements of multi-injection strategies of common rail systems. Additionally common global models for several constant coolant water temperature levels are generated and the workflow tool supports the combination and segmentation of global nominal map with temperature correction maps for seamless and direct ECU setting.

This paper describes the development and application of a newly developed metric for evaluating and quantifying the capability of a vehicle/controller (e.g., Automated Vehicle or human driver) to avoid collisions in nearly any potential scenario, including those involving multiple potential collision partners and roadside objects. At its core, this Collision Avoidance Capability (CAC) metric assesses the vehicle’s ability to avoid potential collisions at any point in time. It can also be evaluated at discrete points, or over time intervals. In addition, the CAC methodology potentially provides a real-time indication of courses of action that could be taken to avoid collisions. The CAC calculation evaluates all possible courses of action within a vehicle’s performance limitations, including combinations of braking, accelerating and steering.

As Advanced Crash Avoidance Technologies (ACATs) such as Forward Collision Warning (FCW), Crash Imminent Braking Systems and other advanced technologies continue to be developed, the need for full-scale test methodologies which can minimize hazards to test personnel and damage to equipment has rapidly increased. The challenge of evaluating such ACAT systems is twofold. First, the evaluation system must be able to deliver a potential Collision Partner (CP) reliably and precisely along a trajectory which would ultimately result in a crash in a variety of configurations, such as rear-ends, head-ons, crossing paths, and sideswipes. Second, and more importantly, the collision partner must not pose a substantial physical risk to the test driver, other test personnel, equipment, or to test vehicles in the event that the collision is not avoided.

The Advanced Crash Avoidance Technologies (ACAT) program initiated by the National Highway Traffic Safety Administration had two major overall objectives. These were to develop a standardized Safety Impact Methodology (SIM) tool to evaluate the effectiveness of advanced technologies in avoiding and mitigating specific types of vehicle crashes; and to develop and demonstrate objective tests that are used in the SIM to verify the safety impact of a real system. Honda and Dynamic Research Inc. (DRI) had been developing and applying such SIMs for several years and had a Cooperative Agreement with NHTSA to further develop a SIM in order to determine the feasibility of developing estimates of effectiveness for specific not-yet-deployed safety technologies in the absence of data from real world or field operational tests, and linking it to the results from objective tests.

This paper reports on the interim progress of the Honda-DRI ACAT-II program initiated by the National Highway Traffic Safety Administration (NHTSA). The objectives of the ACAT-II program were further development of a formalized Safety Impact Methodology (SIM) for estimating the capability of advanced technology applications installed in vehicles to address specific types of motor vehicle crashes, and to evaluate driver acceptance of the technologies. This particular ACAT study extended earlier work by Honda and DRI in the NHTSA ACAT-I program by extending the SIM so as to be able to analyze head-on crashes more completely, and by using the extended SIM to evaluate of a pre-production version of a Honda Head-on Crash Avoidance Assist System (HCAAS).

The Advanced Crash Avoidance Technologies (ACAT) program initiated by the National Highway Safety Administration had two major objectives. These were to develop a standardized Safety Impact Methodology (SIM) tool to evaluate the effectiveness of advanced technologies in avoiding and mitigating specific types of vehicle crashes; and to develop and demonstrate objective tests that are used in the SIM to verify the safety impact of a real system. Honda and Dynamic Research Inc. (DRI) have been developing and applying such SIMs for several years and have a Cooperative Agreement with NHTSA to further develop a SIM that provides an estimate of full systems safety benefits at a national level.

Today's calibration process for ECU functions is often based on a wide variety of proprietary tools and individual expert knowledge of calibration engineers. Automatic calibration with an industrialized tool chain provides high potential to reduce testbed time, calibration time and project costs. Based on an efficient measurement procedure in combination with an offline calibration methodology the capability is validated, e.g. for calibrating the ECU function “Air Charge Determination” for SI engines. In this article the implementation, in a series production project of a major OEM, is shown. The whole workflow - which can also be applied to other calibration tasks - will be described in detail. Presented here will be how General Motors Corporation (GM) is able to speed up the calibration of the ECU functions, whilst maintaining at least the same quality of calibration as before, by the use of this tool chain.

A calibration and validation workflow will be presented in this paper, which utilizes common static global models for fuel consumption, NOx and soot. Due to the applicability for warm-up tests, e. g. New European Driving Cycle (NEDC), the models need to predict the temperature influence and will be fitted with measuring data from a conditioned engine test bed. The applied model structure - consisting of a number of global data-based sub-models - is configured especially for the requirements of multi-injection strategies of common rail systems. Additionally common global models for several constant coolant water temperature levels are generated and the workflow tool supports the combination and segmentation of global nominal map with temperature correction maps for seamless and direct ECU setting.