# EETE MAR 2014

The NEW resistor kits from TE Connectivity Available exclusively from RS Components The new resistor kits from TE Connectivity provide a wide range of resistance measurement features for power management, high precision, industrial and general-purpose applications. www.rs-components.com/teresistorkits lation will enable us to investigate and optimize these new architectures before we spend time implementing them. Using the right tool for the Job We use a portfolio of simulation tools to suit the task in hand. For mathematical modeling of signal flow or behavior we use MATLAB/Simulink. For modeling hydraulics systems we use AMEsim. As soon as we get away from modeling control algorithms and into the electronics Fig. 3: Example of a BH curve taken from the Magnetic Component tool in Saber. domain, then Saber is our tool of choice. Saber supports the concept of conserved system modeling, which allows us to analyze the effects of how one block loads another — something that’s not possible using a signal-flow analysis. Saber also allows us to model events and event transfers, whereas SPICE simulation, for example, uses the continuous (Laplace) domain. Case study: modeling a gasoline pump The physical system of a gasoline fuel pump as shown in figure 2 consists of three parts: a driver circuit simulated using an electromechanical simulator, and separate pump and inlet valve models, which are simulated using the hydraulics simulator. To create the multi-domain simulation shown in figure 2 we used Simulink to model the control part of the ECU algorithm and deployed a combination of Saber and AMEsim (simulating the hydraulics of the fuel pump) to model the plant. It’s a common misconception that Saber is only useful for modeling a system’s power electronics; it actually does a very good job of modeling the electromechanical parts of the system. For example, by getting accurate readings of the force from the electromagnetic circuitry for a solenoid, we can use it to send out a force and receive back a position. We used proportional-integral (PI) control to generate the controller output based on the difference between the target pressure and the pressure feedback at a constant battery voltage input level. Triggering the solenoid in response to the controller output uses energy, so we added pulse width modulation (PWM) duty-cycle control to the original control. While the solenoid had to be fully triggered to open the inlet valve, less force was required for holding it open and therefore we could reduce the current through the solenoid. The percentage reduction in the solenoid current was determined by the PWM duty factor. Following several tests and using our experience, we gathered data on the relationship between the duty factor for various start angles and the revolutions per minute (RPM) and battery voltage. We then produced a look-up table that could be used to obtain the duty-cycle value. The PWM-based control also enabled the use of the virtual CPU based approach for implementing this CPS. We also use Saber to analyze the first-order hysteresis effects of magnetic circuits – see figure 3. This is much simpler and less time consuming than performing a finite element analysis, which has its place if you need to look at fringe effects, but otherwise Saber gives us the right level of detail for system modeling without too much complexity. The future of modeling Given our globally distributed teams, we’re very interested in the emergence of cloud computing to harness global CPU resources and enable us to share higher fidelity models across distributed teams. Today, we are using the cloud to deploy product lifetime management (PLM) applications, but with an increased use of simulation and co-simulation over the next 10 years we can see our use of the cloud transitioning from a manager’s tool to an engineer’s tool. Increasingly, we are encouraging the use of virtual CPU modeling, which involves developing a software model of the microcontroller hardware itself. We can then integrate the microcontroller model with the behavioral models of the plant (the physical system) so that we can perform realistic system performance measurement and validation. This approach allows concurrent development of the plant models and control software applications, and also their validation, including the real-time operating system (RTOS) and device drivers. www.electronics-eetimes.com Electronic Engineering Times Europe March 2014 33

EETE MAR 2014