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EDA SPECIAL Model-based design of multi-physics automotive systems By Sujit S. Phatak and DJ McCune today ’s vehicles epitomize the concept of multi-physics systems. Design teams are bringing together software and electronics, along with airflow and environmental sensors, mechatronic, hydraulic and pneumatic subsystems, to create increasingly sophisticated automotive systems. Traditionally, the automotive industry has made extensive use of “downstream” engineering. Design teams have followed the traditional “V-cycle”, which splits the engineering process into two phases — design and implementation followed by validation. While design teams can benefit significantly from earlier validation of their concepts, the industry has historically favored physical prototyping as a means of validating the design, which requires a commitment to build a hardware prototype early in the project lifecycle. This is often followed by a sequence of reworking, patching and more prototyping. Design teams pursue this cycle until the design appears to be bug-free. Unfortunately, such a downstream approach to engineering can lead to periods of prolonged patch fixing while engineers chase their tails and lose production cycles. If we cannot fix the design by patching, it may require a complete re-design. In the worst case, we may not discover the problem until the vehicle is in production, which can lead to disastrous product recalls. Upfront engineering While simulation doesn’t remove the need for physical prototyping, it does considerably reduce the number of prototyping cycles that we need to go through during a project. By spending more time upfront with the design, we avoid many of the downstream problems. Simulation enables us to learn more about the system and understand how it works. Because simulation models give us better visibility into the way our designs work conceptually, we can get rid of bugs — hopefully before we build them into the prototype. An additional benefit is the ability for new team members to get up to speed with the design by experimenting with the simulation, which doesn’t risk causing damage to (expensive) physical prototypes. Cyber-physical systems A model-based cyber-physical systems (CPSs) development approach as shown in figure 1 enables design teams to integrate physical processes with computational systems during simulation. These virtual CPSs support abstractions appropriate for modeling and design, and analysis techniques suitable for integrated systems. The mechatronic control systems that are implemented in Fig. 1: Simplified block diagram of cyber-physical system (CPS) showing close integration between physical systems (plant) and computational systems (ECU — electronic control unit). automotive applications include those used for engine control, transmission control, throttle control and braking. These typically involve multiple complex physical systems with dedicated embedded controllers that communicate with each other via a vehicle network, such as Controller Area Network (CAN) or FlexRay. We have adopted model-based design for CPSs to improve the efficiency of the design process for these complex systems. During the system design stage we integrate models of physical system behavior (also called “plant models”) with controller models to produce an abstracted system implementation. Accelerating project schedules Simulation enables us to fix bugs before they manifest themselves as problems. That can sometimes make it difficult to put a value on our use of simulation in terms of the engineering time saved or improved design quality. However, a typical prototyping cycle might take us approximately six months. By introducing a model-based CPS, we can reduce that to around two months by breaking the “prototype/ bug-fix” cycle. For derivative projects, we will typically go through two or more prototyping spins to accommodate new requirements, while updating the simulation models will often only take a couple of days. We are also interested in the use of model-based design for more experimental work. For example, we are considering the use of multicore devices for our next-generation advanced architectures, which we don’t use in our products today. Simu- Sujit S. Phatak is responsible for development of virtual prototyping systems at Hitachi America’s Automotive Products Research Laboratory – www.hitachi.com DJ McCune is Group Leader/Senior Researcher for the Embedded Systems Group at Hitachi America R&D – www.hitachi.com Fig. 2: The block diagram of the gasoline fuel pump system and its simulation model represents a multi-domain implementation with a co-simulation bus. 32 Electronic Engineering Times Europe March 2014 www.electronics-eetimes.com


EETE MAR 2014
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