Visteon Simplifies Automotive Powertrain Control Using the NI LabVIEW Control Design and Simulation Module

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"Two primary advantages of LabVIEW over other software packages currently used in the automotive industry are the LabVIEW front panel that serves as a powerful user interface and the graphical development environment, which eliminates the need for lower-level programming. "

- Arek Dutka, Industrial Systems and Control Limited

The Challenge:
Simulating multiple variables to validate complex automotive engine designs to achieve the best fuel economy, engine performance, and emissions control.

The Solution:
Using the NI LabVIEW Control Design and Simulation Module, we developed a real-time control, analysis, and testing application.

Author(s):
Arek Dutka - Industrial Systems and Control Limited
Gustav Ferrao - Industrial Systems and Control Limited

Modern automotive powertrain control systems must continue to evolve to satisfy requirements including regulating exhaust emissions to meet increasingly stringent standards; providing improved fuel economy to comply with corporate average fuel economy (CAFE) regulations, and meeting customer demands for performance and comfort. These objectives are interrelated and often conflict. For example, lean-burn technology can reduce fuel consumption significantly, but it also reduces the three-way catalytic conversion efficiency causing additional air pollution.

Modern automobile regulations can be satisfied by improving existing architectures or introducing new mechanical designs with increased complexity. The camshaft profile is the most important design parameter in determining the performance of an engine. While some engines are designed to meet torque requirements and others are optimized for speed, no single profile can test for all design parameters.

There are four variable cam timing strategies for double overhead camshaft engines (DOHC):

• Phasing only the intake cam (intake only)
• Phasing only the exhaust cam (exhaust only)
• Phasing the exhaust and intake cam equally (dual equal)
• Phasing the exhaust and intake cam independently (twin-independent)

In a twin-independent variable camshaft timing (TIVCT) engine, both the intake and exhaust camshafts are adjusted independently. The variation is a function of throttle position and engine speed. Because the system offers a large number of degrees of freedom for obtaining engine performance, a method is required for optimizing the valve-timing parameters for the best fuel economy, engine performance, and emission control. However, this technique results in a highly complex real-time control algorithm. Although TIVCT was introduced in automotive engines a few years ago, it continues to be a focal point of research and development today.

Real-Time Control, Analysis, and Testing with LabVIEW

Our project is based on the TIVCT engine modeling and the design of an optimal controller to meet specific engine performance objectives. The purpose of the control strategy is to provide the engine with torque reference tracking while minimizing brake-specific fuel consumption and optimizing combustion stability.

We used the LabVIEW Control Design and Simulation Module with the linear algebra VIs from LabVIEW. Two primary advantages of LabVIEW over other software packages currently used in the automotive industry are the LabVIEW front panel that serves as a powerful user interface and the graphical development environment, which eliminates the need for lower-level programming. Additionally, the tools for control, design, and simulation easily integrate with a variety of National Instruments hardware to develop real-time control, analysis, and testing applications, making LabVIEW an attractive choice for the automotive sector.

For the engine model, the main manipulated variables for the control system include mass airflow into the intake manifold, independent camshaft positioning of the inlet, and exhaust/valve timing with respect to the crankshaft. The controlled outputs are the engine torque, brake-specific fuel consumption, and the coefficient of variance of indicated mean effective pressure. Other variables influencing the system such as engine speed and engine coolant temperature are treated as external parameters and are used as scheduling variables for control.

Using the LabVIEW Control Design and Simulation Module, the continuous time TIVCT engine model combines a static characteristic of the combustion process with differential equations describing actuators and the intake manifold to obtain a dynamic model. The resulting nonlinear TIVCT engine model with multiple input, multiple output (MIMO) properties was analyzed by manipulating each input variable and exhibited strong cross-interaction between inputs and outputs. A local model was developed for the control application by linearizing the nonlinear model at fixed operating points using LabVIEW.

Using the LabVIEW Front Panel for Interactive Simulation

An advanced optimal controller was designed using the LQR technique in LabVIEW. The controller has two objectives - offset minimization and regulator action. These objectives were achieved by introducing integral action within the loop to remove steady-state errors in the presence of disturbances. To define the performance index and to minimize the output error and rate of change in the output, the gain was obtained using the LabVIEW tools for the TIVCT engine-state feedback and reference tracking using the optimal theory of continuous time systems.

The local controller and linearized model were built and simulated in LabVIEW. The system tracked the engine torque with an accurate steady state value corresponding to the set point while simultaneously minimizing brake-specific fuel consumption (BSFC) and the coefficient of variation in indicated mean effective pressure (COVIMEP). To ensure online response tuning by visual inspection, the Q and R tuning parameters were made available on the front panel, which optimized the interactive simulation feature of LabVIEW.

It is normal to implement the structure of the model and controller in discrete time so it can easily be transferred to computer hardware for final implementation. The discrete controller can either be derived from the designed continuous controller or designed directly in discrete time using the same LQR VI.

Since the model is nonlinear, the optimal gain parameters that produce the desired response at one operating point might not produce a satisfactory response at another operating point. Therefore, gain scheduling can be applied using different sets of optimal gain parameters for different regions of operation of the nonlinear model. The process of gain tuning is streamlined using interactive adjustment of parameters through the front panel.

Author Information:
Arek Dutka
Industrial Systems and Control Limited
50 George St
Glasgow
United Kingdom
Tel: +44 141 553-1111
actc@isc-ltd.com

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