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The goal of this paper is to explore the complete set of single mode hybrid electric powertrain designs that can be generated with one and two planetary gearsets (PGs). Contrary to an automated design exploration approach, an analytically-based manual method is developed to identify all unique design modes for each hybrid electric powertrain architecture (parallel, series, power-split) that can be created with two planetary gearsets, one engine, one vehicle output shaft, two electric machines, and at most two brake clutches. Feasible design modes are generated according to a procedure that provably covers the entire design space.

This paper outlines the characterization of a Li-Ion Iron Phosphate battery pack with nominal voltage of 700V as well as the modeling of this pack as an equivalent electrical circuit (EEC) for the purpose of vehicle simulations. For a higher level of fidelity and accuracy, the equivalent circuit is initially modeled as an R-2RC circuit which consists of a voltage source with one resistor (R) and two resistor-capacitor (RC) branches. In this modeling effort, first, several open circuit voltage (OCV) determination methods in the literature are benchmarked and state-of-charge (SOC) dependent OCV curve which is used in the voltage source of the EEC model is derived. Then, two methods of parameter estimation of the EEC are developed for both step current and dynamic current profiles. The first estimation method is applicable to discharge or charge step currents and relies mostly on the relaxation portion of the battery response and involves some manual calibration.

The increasing numbers of hybrid electric and full electric vehicle models currently in the market or in the pipeline of automotive OEMs require creative testing mechanisms to drive down development costs and optimize the efficiency of these vehicles. In this paper, such a testing mechanism that has been successfully implemented at the US Environmental Protection Agency National Vehicle and Fuel Emissions Laboratory (EPA NVFEL) is described. In this testing scheme, the units-under-test consist of a battery pack and its associated battery management system (BMS). The remaining subsystems, components, and environment of the vehicle are virtual and modeled in high fidelity.

The focus of this paper is an air charge estimator for engine control system applications which do not feature a mass air flow (MAF) sensor. The proposed approach, beyond its independency of a MAF sensor, is designed to be compatible with the confines of a typical production control system configuration. The air charge estimation algorithm is based on mean-value models for the manifold pressure dynamics and the gas flows through the throttle and valve orifices. It involves nominal static models for the volumetric efficiency of the engine and for the throttle discharge coefficient. The static models for those parameters are complemented with correction factors that are adjusted on-line. The update of the volumetric efficiency correction is implemented in the form of a Kalman-filter which uses the difference between the measured and the modeled manifold pressure as an error metric.

This paper presents a comprehensive Matlab/Simulink-based framework that affords a rapid, systematic, and efficient engine control system development process including automated code generation. The proposed framework hinges on three essential pillars: 1 ) an accurate model for the target engine, 2) a toolset for systematic control design, and 3) a modular system architecture that enhances feature reusability and rapid algorithm deployment. The proposed framework promotes systematic model-based algorithm development and validation in virtual reality. Within this context, the framework affords integration and evaluation of the entire control system at an early development stage, seamless transitions across inherently incompatible product development stages, and rapid code generation for production target hardware.

The fierce competition and shifting consumer demands require automotive companies to be more efficient in all aspects of vehicle development and specifically in the area of embedded engine control system development. In order to reduce development cost, shorten time-to-market, and meet more stringent emission regulations without sacrificing quality, the increasingly complex control algorithms must be transportable and reusable. Within an efficient development process it is necessary that the algorithms can be seamlessly moved throughout different development stages and that they can be easily reused for different applications. In this paper, we propose a flexible engine control architecture that greatly boosts development efficiency.

In GM R&D Powertrain/Engine Control Group, rapid prototyping controller (RPC) systems with Matlab/Simulink are used extensively to design, simulate and implement advanced engine control algorithms and models. However, those RPC systems use powerful microprocessors with large amounts of RAM contrary to engine control modules (ECM) in production vehicles. Therefore, a thorough analysis on the comparatively much more complicated algorithms and models cannot be performed during the research stage, since there are not enough tools to enable the smooth transition from Matlab/Simulink to the production type processor. The Real-Time Interface (RTI) Blockset for a production like microprocessor would close the transition gap between rapid prototyping controller systems and production type microprocessors by leveraging the power and popularity of Matlab/Simulink in control engineering world and automatic code generation tools.

A rapid prototyping controller (RPC) based, full-authority, diesel control system is developed, implemented, tested and validated on FTP cycle. As rapid prototyping controller, dSPACE Autobox is coupled with a fast processor based slave for lower level I/O control and a collection of in-house designed interface cards for signal conditioning. The base software set implemented mimics the current production code for a production diesel engine. This is done to facilitate realistic and accurate comparison of production algorithms with new control algorithms to be added on future products. The engine is equipped with all the state-of-the art subsystems found in a modern diesel engine (common rail fuel injection, EGR, Turbocharger etc.).