Towards a Seamless Development Process for Automotive Engine Control System

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Control Engineering Practice 12 (2004) 977986

Towards a seamless development process for automotive

engine-control system

Wootaik Lee, Seungbum Park, Myoungho Sunwoo*

Automotive Control & Electronics Laboratory, Department of Automotive Engineering, Hanyang University, 17 Haengdang-Dong, Seongdong-Gu,

Seoul 133-791, South Korea

Received 24 March 2003; accepted 26 November 2003

Abstract

This paper describes a new development platform for an automotive engine-control system and introduces a seamless

development process with a practical example of model-based engine control. The development platform consists of a target-

identical rapid control prototyping (RCP) system and a PC-based hardware-in-the loop simulation equipment. This RCP system is

designed very similarly to the real production controller with the help of a customized target package and powerful microcontrollers.

This RCP system insures rapidity of production as well as prototyping, by adopting a target-identical microprocessor. The resulting

target identity is important from the viewpoint of practice and application. An organized development environment is provided by

matching hardware-in-the-loop simulation (HILS) equipment with the RCP system. A control system can be easily tested and

validated using PC-based HILS that uses commercial-off-the-shelf I/O boards. The development platform supports enhanced

concurrent engineering, and results in a reduction of development time and cost. To examine the feasibilities of the proposed

development environment, a model-based air-to-fuel ratio controller based on a sliding mode control scheme is implemented as a

practical example.

r 2004 Elsevier Ltd. All rights reserved.

Keywords: Engine-control systems; Hardware-in-the-loop simulation; Rapid control prototyping

1. Introduction

Automotive electronics have been changed dramati-

cally recently, and new features have been introduced to

satisfy customer expectations. Moreover, the require-

ments for existing functions are becoming more

demanding because of the stricter environmental man-

datory regulations and safety standards. Engine-control

tasks, that were classically solved mechanically, are now

being replaced by electronic control systems, and the

design and implementation of control algorithms is a

crucial element in the development of automotive

engine-control systems. The pressure on the develop-

ment process of electronic engine-control systems has

increased rapidly because engineers are expected to

implement more features in a less time. Ad hoc heuristic

design and implementation methods are being replaced

by systematic requirements-driven processes.

In the last decade, researchers have enhanced the

development process of the control system efficiently in

both academia and industry. The requirements of the

modern development process have been the subject of

many studies. Isermann (1996) examined the importance

of a systematic development process and software tools

for the design. Hanselmann (1998) suggested that the

modern development process is characterized by com-

puter-aided support in all stages from specification to

product. Smith (1999) also proposed that a more

efficient development process is not intended to change

the basic steps. Rather, improved software and hard-

ware tools can make the process more efficient.

Browne, Bass, Croll, and Fleming (1994) and Hajji

et al. (1996) proposed a framework of tools which allow

the design of distributed, potentially fault-tolerant, real-

time control software. Kimura and Maeda (1996) also

introduced two development tools for an engine-control

system. One is the engine and vehicle simulator and the

other is the control logic simulator substituting for a

ARTICLE IN PRESS

*Corresponding author. Tel: +82-2-2290-0453; fax: +82-2-2297-

5495.

E-mail addresses: [email protected] (W. Lee),

[email protected] (S. Park), [email protected]

(M. Sunwoo).

0967-0661/$- see front matterr 2004 Elsevier Ltd. All rights reserved.

doi:10.1016/j.conengprac.2003.11.016


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part of the engine-control logic in production CPUs.

Butts (1996) benchmarked many computer-aided con-

trol system design (CACSD) tools and computer-aided

software/systems engineering (CASE) tools to be

adopted in the modern development process. Tradi-

tional CASE and CACSD tools were integrated to

improve hybrid systems development support for theautomotive power train control community, and CASE/

CACSD products were applied to a simplified power

train system model to investigate the feasibilities.

Toeppe, Bostic, Ranville, and Rzemien (1999) per-

formed a trial evaluation of commercially available

CACSD tools, and Howold and Jupfer (2000) compared

classical CASE-tools approach and tools for automated

code generation.

Some companies offer sophisticated development

environments for automotive applications (Hansel-

mann, 1998; Leharth, Baum, Beck, Werther, & Zur-

awka, 1998). They support the specification of

embedded systems, and verify and validate it on

different abstraction levels. They also generate a code

automatically for rapid control prototyping (RCP)

controllers, and provide a hardware-in-the-loop simula-

tion (HILS) experimental environment.

This paper presents a new integrated platform-based

development environment for automotive engine-con-

trol system. The control algorithms can be developed by

using the MATLABs/SIMULINKs off-line simulation

environment. This control design can be easily imple-

mented in the proposed RCP platform through the

REAL-TIME WORKSHOPs and the customized

target package. The generated execution codes areeffectively tested and verified by using PC-based HILS.

The proposed platform-based environment enables the

developers to design control laws, to generate executable

code, and to test the control system in a unified way, and

make the development process more seamless.

The modern development process is introduced and

the way to enhance the development process is proposed

in the following section. The features of a newly

proposed development platform are explained in detail

in the next section. The results from the pilot project of

an air-to-fuel ratio (AFR) control using the developed

platform are presented to illustrate the feasibilities of the

proposed development environment.

2. Development process

The major characteristics of the traditional develop-

ment process are described as follows: (i) conventional

textual specifications, (ii) a lack of comprehensive tools,

(iii) a sequential approach. The inefficient traditional

development process is being replaced with a modern

development process, which is characterized by an

integrated computer tool chain in all stages from the

specification to the final product.

2.1. Conventional development process V-model

The modern development process can replace the

expensive prototypes with the appropriate alternativesand provide an economical virtual test environment to

minimize the expensive and time-consuming experi-

ments on the test bench or in-vehicle. Furthermore,

the modern development process eliminates an error-

prone hand-coding process.

Sivashankar and Butts (1999) and Smith (1999)

addressed the modern development process in the form

of a simplified V-model (see Fig. 1), and summarized the

requirements of each development phase, respectively.

On the left downward path, development becomes more

detailed and concrete, eventually leading to the compo-

nent. The right upward path leads to the final

production electronic control unit (ECU), which is then

compared to the original ideas, objectives and specifica-

tions.

At the beginning of a new project, the overall system

functionalities are specified. After the initial concept

phase, the requirements of each subsystem are defined

according to the project characteristics. These require-

ments are analyzed and the core functions and features

of each subsystem are specified.

Control algorithms are primarily designed in response

to the pre-defined specifications, and they are also made

robust with respect to extreme and abnormal operating

conditions. A number of architectures and softwaredesign requirements are incorporated. A modeling work

of both the physical plant and the control system occurs

in this stage. This is the most mature stage in the

development process. Advanced modeling tools are well

established and offer powerful graphical user interface

and modeling capabilities. These tools can be smoothly

integrated into the development process.

The control algorithm is implemented in the form of

source codes through a traditional hand-coding or an

auto code-generation method, and is validated with its

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Fig. 1. Modern development process V-model.

W. Lee et al. / Control Engineering Practice 12 (2004) 977986978


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requirements, using a software-in-the-loop simulation

(SILS) method or an RCP method. As in the case of the

modeling and simulation phase, both the SILS and RCP

environment are used to represent the actual system as

much as possible. RCP including an automatic code

generator is the key step for the modern development

process. With the help of the RCP environment, thecontrol engineers can easily validate and verify their

own controller design in the vehicle or in the special test-

benches, without the intervention of software or hard-

ware specialists.

The next step is the modification of the source codes

to an appropriate form for the production target

processor. Converting the control algorithms to the

production level codes is a very time-consuming and

tedious phase.

After the functions are integrated in the production

target, they should be tested against the above-

mentioned functional requirements. Integrated control

systems can be tested and verified using the specially

designed test benches or real vehicles. As an alternative,

a real-time model-based testing procedure, which is

called HILS, may be used. HILS is characterized by the

operation of real components in connection with real-

time simulated components. Usually, the control system

hardware and software is the real system, and the

controlled process can be either fully or partially

simulated.

Final validation and testing will always be required in

the completed system. At the end of the design process,

the control system is finally calibrated for the specific

application using the HILS and the in-vehicle testprocedures. This phase has shown the greatest advance

in the development process.

2.2. Proposed V-model for engine-control system

This RCP equipment enables the control engineers to

verify their own control algorithm in an ideal environ-

ment using an automatic code-generation technique. In

the target implementation phase, this control algorithm

is coded and linked with other parts of the software by

the software engineers. This final software is validated

against the pre-defined requirements or specifications to

check the feasibilities of the target implementation in the

HILS phase. The described V-model can be enhanced

more seamlessly in an application-specific case. A

development platform, which is composed of a target-

identical RCP (Lee, Shin, & Sunwoo, under submission)

and a convenient HILS (Lee, Yoon, & Sunwoo, 2003),

alleviates some technical difficulties in transition from

one phase to another phase (see Fig. 2).

As shown in Fig. 1, the conventional V-model

separates the RCP phase from the target-implementa-

tion phase due to the insufficient computing power of a

target microprocessor and the difference of the abstrac-

tion levels of CACSD tools. The computing power

difference can be alleviated by the recent advent of

powerful floating-point microcontrollers, which are

currently used in high-end engine-control applications.

Furthermore, the difference in the abstraction levels can

also be overcome by some CACSD tools, which have an

automatic code-generation function and provide a

flexible environment for integrating source codes. The

powerful microcontrollers and these CACSD tools

make a target-identical RCP viable in the engine-control

application in spite of its immaturity. The target-

identical RCP also makes control validation easier. This

conventional V-model has two different phases to

validate the control algorithms. One is the control

verification phase, in which only the control algorithm

can be tested by use of an RCP equipment, and the other

is the control validation phase, in which the whole

control system may be tested, including control algo-

rithm and software implementation, by use of a target

ECU. The target-identical RCP can constitute thefinal control system as easily as the RCP in the context

of Fig. 1. Therefore, it makes the former validation

phase redundant, and renders the later validation phase

as easy as the former one.

The conventional V-model enables software engineers

to code the application part after the control algorithm

is verified in the RCP phase. Hand coding of the control

algorithm makes it difficult to shorten the development

time. The automatic code-generation technique, which is

widely used in RCP and HILS, has been developed to

the production-quality level and this technique can be

applied to convert the control algorithm to the execu-

tion code. In spite of the maturity of the automatic code-

generation technique, it is very difficult to generalize the

code-generation procedure of the low layer codes,

because of the hardware dependencies and efficiency of

the codes. The easiness of automatic code generation

can be compromised with the efficiency of hand coding

in the aspect of the layered architecture. The application

part of the software is converted to the codes by the

automatic code-generation technique, and the low layer

codes are programmed by software experts on a trial

and error basis. This compromise makes the control

design and the software design perform concurrently.

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Fig. 2. Proposed V-model for engine-control system.

W. Lee et al. / Control Engineering Practice 12 (2004) 977986 979


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executed in real-time. The Mororola MPC555s is

selected as the target processor. The HILS equipment

is composed of a host computer and a target computer,

which have some data acquisition cards to interface the

physical signals. Fig. 4 shows the block diagram of the

proposed development platform. Although this figure

depicts the RCP host, HILS host, and measurement and

calibration hosts separately, all the programs of the host

computers are executed concurrently in a single host

computer for the developers convenience.

Fig. 5 shows the layered architecture of the proposed

development platform. This RCP platform is designed

for target implementation as well as RCP. To achieve

this goal, layered architecture is strictly maintained and

the RCP platform is designed similarly to the produc-

tion controller. In order to utilize all the features of the

MPC555s, hardware abstraction layer (HAL) is de-

signed as similarly to the target codes as possible. The

middle layer is carefully organized and designed for the

TARGET LANGUAGE COMPILERs realizations.

By use of the implemented scheduler, any task of the

application program can be easily activated in accor-

dance with the pre-defined condition, such as a certain

event or time period. A customized toolbox, called

engine-control toolbox, is developed to interface an

application program, e.g. the control algorithm, with the

lower layer. The frequently used functions are more

abstracted as in a block library form (see Fig. 6). All theblocks are categorized as initialization, I/O functions,

and scheduling functions. The I/O signals of the ECU,

which generally interact with the engine sensors and

actuators at the off-line simulation phase, are replaced

with the appropriate sink and source blocks, such as

rpm read, and update fuel duration. The execution of the

control algorithms can be configured by use of the

trigger blocks and the task subsystem.

To develop a new engine-control system, highly

sophisticated software, calibration, measurement and

diagnosis equipment has to be used. It would be

beneficial to use the same tool for the calibration and

rapid prototyping. CAN calibration protocol (CCP) is

widely used in the automotive industry, and is becoming

a standard tool. Thus, the CCP is selected as a

measurement and calibration tool in this study.

The HILS environment requires signals from the

computational platform to be interfaced with the

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Fig. 4. Hardware block diagram of the development platform.

Fig. 5. Layered architecture of the development platform.

Fig. 6. SIMULINKs toolbox of rapid prototyping platform.



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hardware. In the layered architecture perspective, the

hardware layer can be divided into two categories. One

is the logic-level I/O layer in which the microcontroller

directly interfaces, and the other is the real I/O layer

containing signal conditioning subsystems, power am-

plifying subsystems, and other subsystems. During the

design phase, one must determine the proper portioningof signal processing into available software and hard-

ware. This results in a trade-off among system complex-

ity, computational burden, and maintainability. Though

the lowest hardware interface layer is desired to emulate

more realistic environment, this layer can be by-passed

for the purpose of economy and convenience. If the

logic-level signals, such as the ignition-triggering signal,

can be used instead of real I/O signals, these complicated

devices can be eliminated. In this study, the logic-level I/

O is used and major parts of the by-passed layer are

modeled. For seamless integration of the development

process, xPC targets of REAL-TIME WORKSHOPs

is used in the HILS platform.

4. Engine-control experiments

An engine-control experiment is performed as a pilot

project, to prove the feasibility of the proposed

development process. Two air-to-fuel ratio (AFR)

control algorithms are evaluated in this experiment.

One employs a relatively simple PI control law with a

feed-forward compensation function, and the other

employs a sliding mode fuel injection control law with

a Smith predictor (Yoon, Park, Lee, & Sunwoo, 2001).

4.1. Off-line simulation model

The off-line simulation model mainly consists of anengine model and a controller, as shown in Fig. 7. In this

stage, all SIMULINKs library blocks can be used free

of implementation problems, and a variable-time step

ordinary differential equation solver can be also used for

simulation speed and accuracy. However, it is difficult to

model event-based or crank angle-based controller

behaviors because SIMULINKs basically provides a

time-based simulation method. To model event-based

behavior in a time-based simulation environment,

special simulation mechanisms must be designed, but

this may cause significant overhead in designing and

simulating the model. Therefore, the event-based

behaviors are generally simplified in an off-line simula-

tion phase by minimizing a sampling period to an

affordable value. To increase the accuracy of the

simulation, multi-rate simulation methods are adopted.

Mean value engine models are widely used in

developing model-based engine controllers. Addition-

ally, these engine models are generally appropriate for

the HILS platform. The nonlinear dynamic engine

model, which was introduced in the previous study

(Yoon & Sunwoo, 2001), is used for designing a fuel-

injection controller and HILS.

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Fig. 7. Off-line simulation model using SIMULINKs.



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The controllers are expressed in relatively complicated

differential and algebraic equations. Some equations are

related with engine models, and they are already

expressed in block diagram representation of the engine

model. These are imported from the previous engine

model blocks and other equations are expressed in

combination of SIMULINKs

blocks and user-definedS-functions.

4.2. Engine model and HILS platform

As shown in Fig. 8, the engine model should be

supplemented with analog I/O and timing I/O signal

modules to interface actual signals in real-time. Engine

I/O signals can be categorized into two groups. One

group is composed of analog signals, and the other is

composed of digital signals, including timing signals.

Synchronization of timing I/O signals, such as crank

shaft signal, cam shaft signal, and spark and injectionsignals, with the engine event make the interface more

difficult. Sometimes, these interfaces are achieved

through sophisticated I/O boards with dedicated pro-

cessors. With the help of the powerful computing power

of a PC and efficient kernel of xPC targets, these

synchronized timing I/O signals are interfaced through

the digital I/O and the timing I/O subsystems.

4.3. Control algorithm and RCP platform

Since the engine model can be easily modified for the

HILS platform, the controller can also be altered into an

RCP form with the developed engine-control toolbox

(see Fig. 9).

The major changes are substitution of I/O blocks forthe I/O signals in the off-line simulation. Each I/O block

calls appropriate functions, which are already designed

and implemented in the lower layer. Some blocks and

modules should be replaced with more simple ones

because the generated code should be compact for an

embedded microcontroller and it should be executed in a

timely manner for real-time control. In this case, the

controller is configured to generate a stroke-based event

trigger signal in every engine stroke, to execute the

control algorithm at the same rate.

4.4. Closed-loop experiments

An off-line simulation model is tested under the

proposed development platform (see Fig. 10). The

engine model is executed on the xPC target desktop

PC, and the engine-control algorithm is run on the

target processor. As described previously, all I/O signals

are connected at the logic level.

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Fig. 8. Engine HILS model.



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The results of the off-line simulation and a virtual

experiment using the proposed platform are depicted

and compared in Figs. 11 and 12. In Fig. 11, the PI AFR

control algorithm is tested in the time-based manner,

and the synchronization of the engine is achieved by a

60-2 type crankshaft sensor. On the other hand, in Fig.

12, the sliding mode AFR control law is executed in the

event-based manner, and it is assumed that a 36-1 type

crankshaft sensor is mounted on the engine.

For performance evaluation of the proposed con-

troller, the throttle angle is changed as shown in Figs.

11(a) and 12(a), to simulate a fast tip-in and tip-out

situation that allows the engine to be operated abruptly

between 2000 and 4000 rpm. In addition, the engine

is assumed to be operated under a constant load

condition. The AFR sensor is assumed to have a

measurement delay of two engine cycles because of the

event-based nature of the engine, and it is assumed to

have band-limited white noise.

Figs. 11(c) and 12(c) represent the off-line simulation

results of the models. The off-line simulation model is

also tested under the proposed development platform

and the results are shown in Fig. 11(d) and 12(d).

Compared with the off-line simulation, the performance

of the experiment using the development platform shows

some degradation. A non-zero execution time of the

plant model and the control algorithm, measurement

noise, quantization, and other factors in the experiment

cause this degradation. The different execution period of

the control task also degrades the control performance.

These problems, which may occur in the target

implementation stage and the validation stage, can be

efficiently handled with the help of this virtual develop-

ment environment.

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Fig. 9. Engine controller (using an engine-control toolbox).

Fig. 10. Photograph of the proposed development platform.



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5. Conclusions

A new development platform for automotive engine-

control systems is introduced.

MATLABs/SIMULINKs/REAL-TIME WORK-

SHOPs tool chain is used as a base environment for

implementation and evaluation of the engine controller

as well as the development of the control algorithm.

This platform provides a target-identical RCP platform

and PC-based HILS environment. With the help of a

customized target package and the advent of powerful

microcontollers, the RCP system is organized very

similarly to the real production ECU. This feature

alleviates many implementation problems, which may

occur between the RCP system and the production

system. The control system is easily investigated and

validated using the PC-based HILS system. This system

uses xPC targets with commercially available off-the-

shelf I/O boards and logic-level signals for connection

with the controller. This platform-based development

process enables the developers to design control laws, to

generate executable codes, and to evaluate the control

system in a unified manner.

In order to prove the feasibilities of the proposed

environment, a pilot project for the development of an

air-to-fuel control system is performed, and the simula-

tion results are presented. The simulation results show

that the proposed development process and the virtual

experiment environment can efficiently handle various

ECU design problems caused by transitions among

separate development steps. The proposed environment

can be a basis for the model-based approach in engine-

control application.

References

Browne, A. R., Bass, J. M., Croll, P. R., & Fleming, P. J. (1994). A

prototype framework of design tools for computer-aided control

engineering. IEEE/IFAC joint symposium on computer-aided control

system design, Tucson, AZ (pp. 369374).

Butts, K. R. (1996). An application of integrated CASE/CACSD

to automotive powertrain systems. Proceedings of the 1996

ARTICLE IN PRESS

Fig. 11. Comparison of the off-line simulation and the experiment

using development platform (PI control system, 60-2 type crank signal,

time-based execution).

Fig. 12. Comparison of the off-line simulation and the experiment

using development platform (sliding mode control system, 36-1 typecrank signal, event-based execution).



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IEEE international symposium on CACSD (pp. 339345),

Dearborn, MI.

Hajji, M. S., Bass, J. M., Browne, A. R., Schroder, P., Croll, P. R., &

Fleming, P. J. (1996). The development framework: Work in

progress towards a real-time control system design environment.

IEE Colloquium on Advances in Computer-Aided Control System

Design, London, UK (pp. 4/14/3).

Hanselmann, H. (1998). Development speed-up for electronic controlsystems. Convergence 98, Dearborn, USA.

Howold, C., & Jupfer, R. (2000). Integration of new methods and tools

for automotive control unit developmenta project management

task. SAE2000-01-0392.

Isermann, R. (1996). On the design and control of mechatronic

systemsa survey. IEEE Transactions on Industrial Electronics,

43(1), 415.

Kimura, A., & Maeda, I. (1996). Development of engine control system

using real time simulator. Proceedings of the 1996 IEEE Interna-

tional Symposium on CACSD, Michigan, USA (pp. 157163).

Lee, W., Shin, M., & Sunwoo, M. (under submission). Target-identical

rapid control prototyping platform for model-based engine

control. Proceedings of the Institution of Mechanical Engineers,

Part D. Journal of Automobile Engineering.

Lee, W., Yoon, M., & Sunwoo, M. (2003). A cost- and time-effectivehardware-in-the-loop simulation platform for automotive engine

control systems. Proceedings of the Institution of Mechanical

Engineers, Part D. Journal of Automobile Engineering, 217, 4152.

Leharth, U., Baum, U., Beck, T., Werther, K., & Zurawka, T. (1998).

An integrated approach to rapid product development for

embedded automotive control systems. Control Engineering Prac-

tice, 6, 529540.

Sivashankar, N., & Butts, K. (1999). A modeling environment for

production powertrain controller development. Proceedings of the1999 IEEE international symposium on CACSD (pp. 563568),

Hawaii, USA.

Smith, M.H. (1999). Towards a more efficient approach to automotive

embedded control system development. Proceedings of the 1999

IEEE international symposium on CACSD (pp. 219224), Hawaii,

USA.

Toeppe, S., Bostic, D., Ranville, S., & Rzemien, K. (1999). Automatic

code generation requirements for production automotive power-

train applications. Proceedings of the 1999 IEEE International

Symposium on CACSD (pp. 200206), Hawaii, USA.

Yoon, P., Park, S., Lee, W., & Sunwoo, M. (2001). Robust nonlinear

control of air-to-fuel ratio in spark ignition engines. KSME

International Journal, 15(6), 699708.

Yoon, P., & Sunwoo, M. (2001). A nonlinear dynamic modeling of SI

engines for controller design. International Journal of VehicleDesign, 26(2/3), 277297.

ARTICLE IN PRESS


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