Research Papers

Early Model-Based Design and Verification of Automotive Control System Software Implementations

[+] Author and Article Information
Mahdi Shahbakhti

Mechanical Engineering–Engineering
Mechanics Department,
Michigan Technological University,
Houghton, MI 49931-1295
e-mail: mahdish@mtu.edu

Mohammad Reza Amini

Mechanical Engineering–Engineering
Mechanics Department,
Michigan Technological University,
Houghton, MI 49931-1295
e-mail: mamini@mtu.edu

Jimmy Li

Department of Mechanical Engineering,
University of California,
Berkeley, CA 94720-1740
e-mail: jl2kx@berkeley.edu

Satoshi Asami

Graduate School of Environment and
Information Science,
Yokohama National University,
79-7 Tokiwadai, Hodogaya-ku,
Yokohama 240-8501, Japan
Email: asami-satoshi-nz@ynu.ac.jp

J. Karl Hedrick

Department of Mechanical Engineering,
University of California,
Berkeley, CA 94720-1740
e-mail: khedrick@me.berkeley.edu

1Corresponding author.

Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL. Manuscript received March 12, 2014; final manuscript received June 6, 2014; published online September 10, 2014. Assoc. Editor: Gregory Shaver.

J. Dyn. Sys., Meas., Control 137(2), 021006 (Sep 10, 2014) (14 pages) Paper No: DS-14-1114; doi: 10.1115/1.4027845 History: Received March 12, 2014; Revised June 06, 2014

Verification and validation (V&V) are essential stages in the design cycle of automotive controllers to remove the gap between the designed and implemented controller. In this paper, an early model-based methodology is proposed to reduce the V&V time and improve the robustness of the designed controllers. The application of the proposed methodology is demonstrated on a cold start emission control problem in a midsize passenger car. A nonlinear reduced order model-based controller based on singular perturbation approximation (SPA) is designed to reduce cold start hydrocarbon (HC) emissions from a spark ignition (SI) combustion engine. A model-based simulation platform is created to verify the controller robustness against sampling, quantization, and fixed-point arithmetic imprecision. In addition, the results from early model-based verification are used to identify and remove sources of errors causing propagation of numerical imprecision in the controller structure. Thus the structure of the controller is modified to avoid or to reduce the level of numerical noise in the controller design. The performance of the final modified controller is validated in real-time by testing the control algorithm on a real engine control unit. The validation results indicate the modified controller is 17–63% more robust to different implementation imprecision while it requires lower implementation cost. The proposed methodology from this paper is expected to reduce typical V&V efforts in the development of automotive controllers.

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Fig. 1

Computational flow in a typical fixed-point automotive control system

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Fig. 2

Proposed early model-based V&V methodology

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Fig. 3

Major methods for reducing cold start HC emission in SI engines

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Fig. 4

Comparison between measured and simulated cumulative tailpipe HC emission [38]

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Fig. 5

Process of nonlinear SPA model order reduction

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Fig. 6

HSVs for cold start emission model

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Fig. 7

Control signals for open loop simulations

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Fig. 8

Comparison of tailpipe HC flow rates predictions by full state and reduced models

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Fig. 9

Structure of the designed cold start controller

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Fig. 10

Schematic of the cold start emission control system in this work

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Fig. 11

Cold start performance of the designed controller: (a) temperature, conversion efficiency of the catalytic converter and (b) engine and tailpipe HC emissions

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Fig. 12

Effect of fixed-point data type (word length) on the tracking performance of the cold start controller

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Fig. 13

Effect of data types, quantization levels and sampling rates on the performance of the cold start controller

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Fig. 14

Error propagation in loop design versus no-loop design (implementation specification: 10 ms sampling, 10-bit ADC, 12-bit word length)

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Fig. 15

Schematic of the controller structure in Z space

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Fig. 16

Cold start HCcum tailpipe emissions from the modified (no-loop) cold start controller

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Fig. 17

Processor-in-the-loop setup used for real-time testing of the designed cold start controller

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Fig. 18

Real-time performance of the minimally implemented controller in a real ECU



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