Determining common rail system tolerances using Monte Carlo Method and Design-of-Experiments

A Sommerer, J Gerhardt, U Projahn, J KrauЯ, M Marheineke,

S Nonnenmacher

Robert Bosch GmbH, Diesel Systems, Germany


Common rail systems provide fuel at a defined rate, pressure and time. These parameters vary from system to system, injector to injector, shot to shot due to component and subcomponent tolerances. A precise forecast of these tolerances can pose a challenge especially in the presence of learning functions that are designed to improve system accuracy.

Rail pressure peaks are a consequence of confined control accuracy. They impose durability requirements upon affected components like rail, injector and pump. The tolerance calculation scheme described in this paper is based on the well-known Monte Carlo Method (MCM). The software function considered is implemented into the algorithm as Matlab code. In order to provide a mathematical description of the high pressure pump and its fuel metering unit a data-based model has been created, based on Design-of-Experiments measurements. This analysis allows to consider a large number of influence parameters.

This article contains a detailed description of the calculation scheme as well as the applied tools. A comparison of the system performance with and without the supporting software function concludes the investigation.


Common rail systems (CRS) are the state of the art engine management technology for Diesel powered passenger cars and commercial vehicles. CRS accurately provide injection quantities at a defined rate, pressure and time. The objective is an optimum in-cylinder combustion process regarding emissions, driveability and fuel consumption while maintaining structural system integrity. Deviations from nominal values can lead to emission legislation violation, shortcomings in vehicle driveability or structural damage of system components. Tolerances can be kept small by using a mechatronically smart component design in combination with software functions that use available sensor information to further improve system performance. This approach represents the core of "systems engineering" (l). A fundamental feature of common rail systems is the capability to provide the whole range of rail pressure independently of the current operation point. Speed, stability and accuracy of the corresponding pressure control algorithm are quality attributes of the system.

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