Managing Complexity in Large Scale

Control System Design

 

Anthony Phillips

 

Project Leader, Advanced Vehicle System Control

Propulsion System Engineering Dept.

Research and Advanced Engineering

Ford Motor Company

 

Abstract:  Automotive controls have historically been limited to the powertrain (engine and transmission) and brake systems within the vehicle with only minimal communication between them. As customer and regulatory demands in the areas of performance, fuel economy, and emissions continue to grow, the need for more sophistication and coordination within the vehicle increases. Automakers are responding by leveraging cost and speed improvements in microprocessors and communication networks that enable the introduction of more advanced subsystems (e.g. advanced vehicle stability control systems and hybrid vehicle powertrains). Managing the control system development and coordination of these new systems is rapidly becoming more complex. At the same time, the faster development times being dictated by today's economic environment require more reusability and portability of controller software from one project to the next.

 

The Advanced Vehicle System Control (VSC) team in Ford's Research and Advanced Engineering has been using a new process for developing advanced vehicle control solutions. The process is oriented on a functional approach. Specifically, the vehicle control system is broken down into "atomic" functions that are portable and reusable and that have standard, generic interfaces. To facilitate this functional management process, a database tool is under development for tracking the functions, signals, code releases, and hardware allocations for each new project. The enumerated functions in the database also map directly to the Simulink (implementation) models of the control systems. The talk will focus on describing the functional management process and how it has been applied to several recent advanced hybrid vehicle projects.

 

Friday, October 17, 2003

3:30 – 4:30 p.m.

1500 EECS