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Design, Implementation and Testing of a Spark-Ignition Engine Management System

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Abstract

The engine management system (EMS) is arguably one of the most critical and complex components of a spark ignition (SI) engine. Modern EMS incorporates various components (like sensors, actuators, control strategies, etc.) to achieve an appropriate engine response. Even though EMS has been researched for a long time, most existing studies have just focused on individual control modules with no consideration about their interaction or how they work when brought together. For this reason, this paper presents the entire design, implementation and testing of EMS for a SI system. In particular, this investigation shows each EMS module, along with tests of the EMS. In addition, we carried out numerous experimental tests (such as stability analysis, reference tracking, and disturbance rejection) to assess the custom EMS. From vehicle performance test, we obtained a slight power (1.2%) and torque (1.3%) percentage errors between custom and original EMS. Similarly, percentage error obtained for vehicle emission tests for hydrocarbons (HC), carbon monoxide (CO), and nitrogen oxides (NOx) are 29.2%, 21.4% and 65.9%, respectively, which highlighted a slightly richer mixture once compared to custom with the original EMS. Lastly, experiment results show the success of the proposed EMS.

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Notes

  1. Coefficients a and b may change due to ambient pressure and intake air temperature.

  2. Atmospheric pressure and temperature could also influence engine performance and reference torque.

References

  • Ahmed, Q., & Bhatti, A. I. (2010). Estimating SI engine efficiencies and parameters in second-order sliding modes. IEEE Transactions on Industrial Electronics, 58(10), 4837–4846.

    Article  Google Scholar 

  • Ahn, K.-H., Stefanopoulou, A. G., & Jankovic, M. (2012). AFR-based fuel ethanol content estimation in flex-fuel engines tolerant to MAF sensor drifts. IEEE Transactions on Control Systems Technology, 21(3), 590–603.

    Article  Google Scholar 

  • Ajmir, M., Elmi, A., Nazir, A. M., & Asyraf, J. M. N. (2019). Automated spark ignition timing controller (ASITC) for internal combustion engine control unit. IOP Conference Series: Materials Science and Engineering, 501(1), 012012.

    Article  Google Scholar 

  • Amorim, R. J., Valle, R. M., Baeta, J. G. C., Barros, J. E. M., & de Carvalho, R. D. B. (2005). Spark ignition engine performance using several alcohol concentrations in gasoline and CNG. SAE Technical Paper, Tech: Rep.

    Google Scholar 

  • Anand, G., Gopinath, S., Ravi, M., Kar, I., & Subrahmanyam, J. (2006). Artificial neural networks for prediction of efficiency and NOx emission of a spark ignition engine. SAE Technical Paper, Tech: Rep.

    Google Scholar 

  • Ashok, B., et al. (2017). An integrated pedal follower and torque based approach for electronic throttle control in a motorcycle engine. Engineering Journal, 21, 63–80.

    Article  Google Scholar 

  • Ashok, B., Ashok, S., & Kavitha, C. (2018). Closed loop throttle opening angle estimation strategy by considering torque demands from SI engine. SAE Technical Paper, Tech: Rep.

    Google Scholar 

  • Ashok, B., Ashok, S. D., & Kumar, C. R. (2016). A review on control system architecture of a SI engine management system. Annual Reviews in Control, 41, 94–118.

    Article  Google Scholar 

  • Ashok, B., Ashok, S. D., & Kumar, C. R. (2017). Trends and future perspectives of electronic throttle control system in a spark ignition engine. Annual Reviews in Control, 44, 97–115.

    Article  Google Scholar 

  • Ashok, B., Ashok, S., Kumar, C., & Kavitha, C. (2019). Neural network based virtual sensor for throttle valve position estimation in a SI engine. SAE Technical Paper, Tech: Rep.

    Book  Google Scholar 

  • Barlow, T. J., Latham, S., McCrae, I., & Boulter, P. (2009). A reference book of driving cycles for use in the measurement of road vehicle emissions. TRL Published Project Report.

  • Borg, J. M., Saikalis, G., Oho, S., Cheok, K. C., & Kurihara, N. (2006). Automatic on-line tuning of the knock detection system on an ecu. IFAC Proceedings Volumes, 39(16), 324–329.

    Article  Google Scholar 

  • Boulat, A., Genninasca, Y., Charlet, A., & Higelin, P. (2001). ECUTEST-A real-time engine simulator for ECU development and testing. SAE Technical Paper, Tech: Rep.

    Book  Google Scholar 

  • Bozhkov, S., Milenov, I., Petrov, R., Leontiev, V., & Bozhkov, P. (2020). Methodology for static tuning of the HEV fuel flow measuring system. IOP Conference Series: Materials Science And Engineering, 939, 012015.

    Article  Google Scholar 

  • Braun, L., Armbruster, M., & Sax, E. (2016). Stakeholder issues concerning the automotive E/E-architecture. In 2016 international conference on electrical systems for aircraft, railway, ship propulsion and road vehicles & international transportation electrification conference (ESARS-ITEC). IEEE, pp. 1–6.

  • Chen, B.-C., Wu, Y.-Y., Tsai, H.-C., & Chen, B.-L. (2014). Development of engine model using modulization method for EMS verification through MIL and HIL. SAE Technical Paper, Tech: Rep.

    Google Scholar 

  • Chevalier, A., Vigild, C. W., & Hendricks, E. (2000). Predicting the port air mass flow of SI engines in air/fuel ratio control applications. SAE Transactions, 109, 183–210.

    Google Scholar 

  • Corti, E., & Forte, C. (2010). A statistical approach to spark advance mapping. Journal of Engineering for Gas Turbines and Power, 132(8), 082803.

    Article  Google Scholar 

  • Da Silva, R. L., Rossetti, P., Santos, J. P. F., Laganá, A. A. M., Colón, D., & Justo, J. F. (2020). Real-time knock characterization using adaptive filters and power estimators. IEEE Access, 8, 84371–84384.

    Article  Google Scholar 

  • Daingade, P.S., & Yadav, S. (2013). Electronically operated fuel supply system to control air fuel ratio of biogas engine. In 2013 international conference on energy efficient technologies for sustainability. IEEE, pp. 740–743.

  • Deur, J., Pavkovic, D., Peric, N., Jansz, M., & Hrovat, D. (2004). An electronic throttle control strategy including compensation of friction and limp-home effects. IEEE Transactions on Industry Applications, 40(3), 821–834.

    Article  Google Scholar 

  • Di Cairano, S., Yanakiev, D., Bemporad, A., Kolmanovsky, I. V., & Hrovat, D. (2012). Model predictive idle speed control: Design, analysis, and experimental evaluation. IEEE Transactions on Control Systems Technology, 20(1), 84–97.

    MATH  Google Scholar 

  • di Gaeta, A., Montanaro, U., & Giglio, V. (2010). Idle speed control of GDI-SI engines via ECU-1D engine co-simulation. SAE Technical Paper, Tech: Rep.

    Google Scholar 

  • Dias, B. M. D. A., Laganá, A. A. M., Justo, J. F., Yoshioka, L. R., Santos, M. M. D., & Gu, Z. (2018). Model-based development of an engine control module for a spark ignition engine. IEEE Access, 6, 53638–53649.

    Article  Google Scholar 

  • Emiliano, P. (2014). Spark ignition feedback control by means of combustion phase indicators on steady and transient operation. Journal of Dynamic Systems, Measurement, and Control, 136(5), 021012.

    Article  Google Scholar 

  • Fleming, B. (2014). An overview of advances in automotive electronics [automotive electronics]. IEEE Vehicular Technology Magazine, 9(1), 4–9.

    Article  Google Scholar 

  • Gao, J., Wu, Y., & Shen, T. (2017). A statistical combustion phase control approach of SI engines. Mechanical Systems and Signal Processing, 85, 218–235.

    Article  Google Scholar 

  • Gibson, A., Kolmanovsky, I., Hrovat, D., &“Application of disturbance observers to automotive engine idle speed control for fuel economy improvement. In (2006) American Control Conference. IEEE, pp. 1197–1202.

  • Guzzella, L., & Onder, C. (2009). Introduction to modeling and control of internal combustion engine systems (2nd ed.). Springer.

    Google Scholar 

  • Jacob, A., & Ashok, B. (2020). An interdisciplinary review on calibration strategies of engine management system for diverse alternative fuels in IC engine applications. Fuel, 278, 118236.

    Article  Google Scholar 

  • Keller, M., Geiger, S., Kluge, K., Günther, M., Pischinger, S., Abel, D., & Albin, T. (2020). Nonlinear MPC for transient charging pressure and egr rate control for a turbocharged SI engine. In 2020 28th Mediterranean conference on control and automation (MED). IEEE, pp. 677–684.

  • Kienberger, J., Schmidhuber, S., Saad, C., Kuntz, S., & Bauer, B. (2017). Parallelizing highly complex engine management systems. Concurrency and Computation: Practice and Experience, 29(15), e4115.

    Article  Google Scholar 

  • Laganá, A. A. M., Lima, L. L., Justo, J. F., Arruda, B. A., & Santos, M. M. D. (2018). Identification of combustion and detonation in spark ignition engines using ion current signal. Fuel, 227, 469–477.

    Article  Google Scholar 

  • Lei, M., Chunnian, Z., Hong, L., Jie, L., Wen, L., & Xianghua, L. (2014). Research on modeling and simulation of SI engine for AFR control application. The Open Automation and Control Systems Journal, 6(1), 803–812.

    Article  Google Scholar 

  • Lejsek, D., & Kulzer, A. (2011). Engine start-up optimization using the transient burn rate analysis. SAE International Journal of Engines, 4(1), 38–49.

    Article  Google Scholar 

  • Liu, F., & Pfeiffer, J. (2015). Estimation algorithms for low pressure cooled EGR in spark-ignition engines. SAE International Journal of Engines, 8(4), 1652–1659.

    Article  Google Scholar 

  • Liu, F., Pfeiffer, J. M., Caudle, R., Marshall, P., & Olin, P. (2016). Low pressure cooled EGR transient estimation and measurement for an turbocharged SI engine. SAE Technical Paper: Tech. Rep.

    Book  Google Scholar 

  • Lopez, V. V., Mejia, J. M. E., & Dominguez, D. E. C. (2017). Design and statistical validation of spark ignition engine electronic control unit for hardware-in-the-loop testing. IEEE Latin America Transactions, 15(8), 1376–1383.

    Article  Google Scholar 

  • Malikopoulos, A. A., Papalambros, P. Y., & Assanis, D. N. (2007). A learning algorithm for optimal internal combustion engine calibration in real time. International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, 48078, 91–100.

    Google Scholar 

  • Mamala, J., Brol, S., & Graba, G. (2013). Hardware-in-the-loop type simulator of spark ignition engine control unit. In 2013 International Symposium on Electrodynamic and Mechatronic Systems (SELM). IEEE, pp. 41–42.

  • Maniscalco, C., Majo, V. Di, Pipitone, E., & Giaconia, G. C. (2016) Design and implementation of an electronic control unit for a CFR Bi-fuel spark ignition engine. In International conference on applications in electronics pervading industry, environment and society. Springer, pp. 77–85.

  • Manivannan, P., Singaperumal, M., & Ramesh, A. (2011). Development of an idle speed engine model using in-cylinder pressure data and an idle speed controller for a small capacity port fuel injected SI engine. International Journal of Automotive Technology, 12(1), 11–20.

    Article  Google Scholar 

  • Ma, H., Noguchi, H., & Williams, P. (2020). Driving cycle based control and calibration for a turbocharged SI engine with low pressure EGR system. SAE Technical Paper, Tech: Rep.

    Book  Google Scholar 

  • Perrone, D., Falbo, L., Castiglione, T., & Bova, S. (2019). Knock mitigation by means of coolant control. SAE Technical Paper, Tech: Rep.

    Book  Google Scholar 

  • Pipitone, E., Beccari, S., & Genchi, G. (2015). A refined model for knock onset prediction in spark ignition engines fueled with mixtures of gasoline and propane. Journal of Engineering for Gas Turbines and Power, 137(11), 111501.

    Article  Google Scholar 

  • Pischinger, S., Schernus, C., Lütkemeyer, G., Theuerkauf, H. J., Winsel, T., & Ayeb, M. (2004). Investigation of predictive models for application in engine cold-start behavior. SAE Technical Paper: Tech. Rep.

    Google Scholar 

  • Potdar, J. S., & Mane, Y. B.(2018) Hardware design and development of engine control unit for four cylinder engine. In 2018 fourth international conference on computing communication control and automation (ICCUBEA). IEEE, pp. 1–5.

  • Rashid, A. K., Abu Mansor, M. R., Ghopa, W. A. W., Harun, Z., & Mahmood, W. M. F. W. (2016). An experimental study of the performance and emissions of spark ignition gasoline engine. International Journal of Automotive & Mechanical Engineering, 13(3), 3540–3554.

    Article  Google Scholar 

  • Rashidi, F. (2017). Adaptive neurofuzzy control of engine idle speed. Journal of Intelligent & Fuzzy Systems, 32(1), 817–829.

    Article  MathSciNet  Google Scholar 

  • Saiteja, P., & Ashok, B. (2022). Critical review on structural architecture, energy control strategies and development process towards optimal energy management in hybrid vehicles. Renewable And Sustainable Energy Reviews, 157, 112038.

    Article  Google Scholar 

  • Schäuffele, J., & Zurawka, T. (2016). Automotive software engineering (2nd ed.). Springer.

    Book  Google Scholar 

  • Shahbakhti, M., Reza Amini, M., Li, J., Asami, S., & Karl Hedrick, J. (2015). Early model-based design and verification of automotive control system software implementations. Journal of Dynamic Systems, Measurement, and Control, 137(2), 021006.

    Article  Google Scholar 

  • Shamekhi, A.-M., Taghavipour, A., & Shamekhi, A. H. (2020). Engine idle speed control using nonlinear multiparametric model predictive control. Optimal Control Applications and Methods, 41(3), 960–979.

    Article  MathSciNet  MATH  Google Scholar 

  • Stobart, R. K., Guo, X., Bartley, G., & Stacey, S. (2011). Exploring the value of open source in SI engine control. SAE Technical Paper, Tech: Rep.

    Google Scholar 

  • Stotsky, A. (2007). Adaptive estimation of the engine friction torque. European Journal of Control, 13(6), 618–624.

    Article  MathSciNet  MATH  Google Scholar 

  • Stotsky, A. A. (2007). Data-driven algorithms for engine friction estimation. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, 221(7), 901–909.

    Google Scholar 

  • Tang, H., Weng, L., Dong, Z. Y., & Yan, R. (2010). Engine control design using globally linearizing control and sliding mode. Transactions of the Institute of Measurement and Control, 32(2), 225–247.

    Article  Google Scholar 

  • Thornhill, M., Thompson, S., & Sindano, H. (2000). A comparison of idle speed control schemes. Control Engineering Practice, 8(5), 519–530.

    Article  Google Scholar 

  • Traub, M., Maier, A., & Barbehön, K. L. (2017). Future automotive architecture and the impact of IT trends. IEEE Software, 34(3), 27–32.

    Article  Google Scholar 

  • Winsel, T., Ayeb, M., Theuerkauf, H. J., Pischinger, S., Schernus, C., & Lütkemeyer, G. (2004). HiL-calibration of SI engine cold start and warm-up using neural real-time model. SAE Technical Paper, Tech: Rep.

    Google Scholar 

  • Wojnar, S., Polóni, T., Šimončič, P., Rohal’-Ilkiv, B., Honek, M., & Csambál, J. (2013). Real-time implementation of multiple model based predictive control strategy to air/fuel ratio of a gasoline engine. Archives of Control Sciences, 23, 93–106.

    Article  MathSciNet  MATH  Google Scholar 

  • Xia, F., Griefnow, P., Tidau, F., Jakoby, M., Klein, S., & Andert, J. (2020). Electric torque assist and supercharging of a downsized gasoline engine in a 48 V mild hybrid powertrain. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, 235(5), 1245–1255.

    Google Scholar 

  • Yao, D.-W., Wu, F., Yang, Z.-J., & Yu, X.-L. (2010). Design of idle speed controller for an SI engine based on incremental digital PID. Journal of Zhejiang University. Engineering Science, 44(6), 1122–1126.

    Google Scholar 

  • Yoon, P., & Sunwoo, M. (2001). A nonlinear dynamic modelling of SI engines for controller design. International Journal of Vehicle Design, 26(2–3), 277–297.

    Article  Google Scholar 

  • Zeng, J., Zhang, L., Kong, F., & Song, X. (2006). Development of 32-bit universal electronic control unit UECU32 for automotive application. In 2006 9th international conference on control, automation, robotics and vision. IEEE, pp. 1–6.

  • Zhu, Q., & Prucka, R. (2019). Integrated engine states estimation using extended Kalman filter and disturbance observer. SAE International Journal of Advances and Current Practices in Mobility,2(2019–01–2603), 929–938.

  • Zhu, Q., Onori, S., & Prucka, R. (2017). An economic nonlinear model predictive control strategy for SI engines: Model-based design and real-time experimental validation. IEEE Transactions on Control Systems Technology, 27(1), 296–310.

    Article  Google Scholar 

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Authors and Affiliations

  1. Departamento de Engenharia de Sistemas Eletrônicos, Escola Politécnica da Universidade de São Paulo, São Paulo, Brazil

    Bruno C. F. Pereira, Bruno S. Pereira, Armando A. M. Laganá & Flávio A. M. Cipparrone

  2. Engenharia Automotiva, Universidade de Brasília, Distrito Federal, Brazil

    Evandro L. S. Teixeira

  3. Departamento de Eletrônica, Universidade Tecnológica Federal do Paraná, Ponta Grossa, Paraná, 84017-220, Brazil

    Max M. D. Santos

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  1. Bruno C. F. Pereira
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Pereira, B.C.F., Pereira, B.S., Teixeira, E.L.S. et al. Design, Implementation and Testing of a Spark-Ignition Engine Management System. J Control Autom Electr Syst 34, 554–565 (2023). https://doi.org/10.1007/s40313-022-00978-z

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