Optimal dynamic calibration methods for powertrain controllers

Emission legislation for passenger cars has become more stringent and the increasing demand for reduced fuel consumption has resulted in the introduction of complex new engine and after-treatment technologies involving significantly more control parameters. Vehicle manufacturers employ a time consuming engine parameter calibration process to optimise vehicle performance through the development of engine management system control maps. The traditional static calibration methods require an exponential increase in calibration time with additional calibration parameters and control objectives. To address this issue, this thesis develops and investigates a novel Inverse Optimal Behaviour Based Dynamic Calibration methodology and its application to diesel engines. This multi-stage methodology is based on dynamic black-box modelling and dynamic system optimisation. Firstly the engine behaviour is characterized by black-box models, based on data obtained in a rapid data collection process, for accurate dynamic representation of a subject engine. Then constrained dynamic optimisation is employed to find the optimal input-output behaviour. Finally the optimal input-output behaviour is used to identify feedforward dynamic controllers. The current study applies the methodology to an industrial state-of-the-art WAVERT model of a 1.5 litre Turbo EU6.1 Diesel engine acting as a virtual engine. The approach directly yields a feedforward controller in a nonlinear polynomial structure which can either be directly implemented in the engine-management system or converted to a dynamic or static look-up table format. The results indicate that the methodology is superior to the conventional static calibration approach in both computing efficiency and control performance. A low-cost Transient Testing Platform is presented in this work to carry out transient data collection experiments on a steady-state dynamometer with application to non-linear engine and emissions modelling using State Space Neural Networks. This modelling technique is shown to be superior to the polynomial models and achieves similar performance to non-linear autoregressive with exogenous input neural (NARMAX) network models. Numerical Dynamic Programming is investigated in a simplified engine calibration problem for a virtual engine to potentially improve the dynamic calibration optimisation stage. In a second study the novel dynamic calibration methodology is applied to the airpath control of a 3.0L Jaguar Land Rover (JLR) turbocharged Diesel engine utilizing a direct optimisation approach and State Space Neural Network models. A complete experimental application of the methodology is demonstrated in a vehicle where the vehicle-implemented calibration is obtained in a one-shot process solely from data obtained from the fast dynamic dynamometer testing. The results obtained demonstrate the potential of this methodology for the rapid development of efficient dynamic feedforward controllers based on limited data from the engine test bed

Design and development of auxiliary components for a new two-stroke, stratified-charge, lean-burn gasoline engine

A unique stepped-piston engine was developed by a group of research engineers at Universiti Teknologi Malaysia (UTM), from 2003 to 2005. The development work undertaken by them engulfs design, prototyping and evaluation over a predetermined period of time which was iterative and challenging in nature. The main objective of the program is to demonstrate local R&D capabilities on small engine work that is able to produce mobile powerhouse of comparable output, having low-fuel consumption and acceptable emission than its crankcase counterpart of similar displacement. A two-stroke engine work was selected as it posses a number of technological challenges, increase in its thermal efficiency, which upon successful undertakings will be useful in assisting the group in future powertrain undertakings in UTM. In its carbureted version, the single-cylinder aircooled engine incorporates a three-port transfer system and a dedicated crankcase breather. These features will enable the prototype to have high induction efficiency and to behave very much a two-stroke engine but equipped with a four-stroke crankcase lubrication system. After a series of analytical work the engine was subjected to a series of laboratory trials. It was also tested on a small watercraft platform with promising indication of its flexibility of use as a prime mover in mobile platform. In an effort to further enhance its technology features, the researchers have also embarked on the development of an add-on auxiliary system. The system comprises of an engine control unit (ECU), a directinjector unit, a dedicated lubricant dispenser unit and an embedded common rail fuel unit. This support system was incorporated onto the engine to demonstrate the finer points of environmental-friendly and fuel economy features. The outcome of this complete package is described in the report, covering the methodology and the final characteristics of the mobile power plant

Meta-heuristic algorithms in car engine design: a literature survey

Meta-heuristic algorithms are often inspired by natural phenomena, including the evolution of species in Darwinian natural selection theory, ant behaviors in biology, flock behaviors of some birds, and annealing in metallurgy. Due to their great potential in solving difficult optimization problems, meta-heuristic algorithms have found their way into automobile engine design. There are different optimization problems arising in different areas of car engine management including calibration, control system, fault diagnosis, and modeling. In this paper we review the state-of-the-art applications of different meta-heuristic algorithms in engine management systems. The review covers a wide range of research, including the application of meta-heuristic algorithms in engine calibration, optimizing engine control systems, engine fault diagnosis, and optimizing different parts of engines and modeling. The meta-heuristic algorithms reviewed in this paper include evolutionary algorithms, evolution strategy, evolutionary programming, genetic programming, differential evolution, estimation of distribution algorithm, ant colony optimization, particle swarm optimization, memetic algorithms, and artificial immune system

Experimental and Numerical Investigation of Engine Foundation for Vibration Reduction

The purpose of this study is to minimise frequency response of engine foundation using topology optimisation. The study involves vibration response estimation of an existing marine engine foundation, validation of estimations with measurements and estimation of reduction in vibration response after optimisation. Initially, solid model of baseline model is generated using dimensions of the existing foundation measured by a laser line probe coordinate measuring machine. Harmonic analysis is used to find the vibration response of the foundation. These results are experimentally validated by the measurements on the foundation using the vibration testing. Frequency response topology optimisation is then carried out on the baseline model to reduce vibration response with specified constraints and objective function. Subsequently, harmonic analysis is performed on the topology optimised design to verify the reduction in vibration response. From these results, it is observed that considerable frequency response is reduced with modified design compared to baseline model

Switching strategy between HP (high pressure)- and LPEGR (low pressure exhaust gas recirculation) systems for reduced fuel consumption and emissions

EGR (Exhaust gas recirculation) plays a major role in current Diesel internal combustion engines as a cost-effective solution to reduce NO emissions. EGR systems will suffer a significant evolution with the introduction of NO after-treatment and the proliferation of more complex EGR architectures such as low pressure EGR or dual EGR. In this paper the combination of HPEGR (high pressure EGR) LPEGR (low pressure EGR) is presented as a method to minimise fuel consumption with reduced NOx emissions. Particularly, the paper proposes to switch between HPEGR and LPEGR architectures depending on the engine operating conditions in order to exploit the potential of both systems. In this sense, given a driving cycle, in the case at hand the NEDC, the proposed strategy seeks the EGR layout to use at each instant of the cycle to minimise the fuel consumption such that NO emissions are kept below a certain limit. The experimental results obtained show that combining both EGR systems sequentially along the NEDC allows to keep NO emission below a much lower limit with minimum fuel consumption.This work has been partially supported by Ministerio de Ciencia y Tecnologia through Project INNPACTO EGRCOEN.Lujan Martinez, JM.; Guardiola García, C.; Pla Moreno, B.; Reig, A. (2015). Switching strategy between HP (high pressure)- and LPEGR (low pressure exhaust gas recirculation) systems for reduced fuel consumption and emissions. Energy. 90:1790-1798. doi:10.1016/j.energy.2015.06.138S179017989

Adaptive calibration of Diesel engine injection for minimising fuel consumption with constrained NOx emissions in actual driving missions

This is the author¿s version of a work that was accepted for publication in International Journal of Engine Research. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published as https://doi.org/10.1177/1468087420918800[EN] This article proposes a method for fuel minimisation of a Diesel engine with constrained NOx emission in actual driving mission. Specifically, the methodology involves three developments: The first is a driving cycle prediction tool which is based on the space-variant transition probability matrix obtained from an actual vehicle speed dataset. Then, a vehicle and an engine model is developed to predict the engine performance depending on the calibration for the estimated driving cycle. Finally, a controller is proposed which adapts the start-of-injection calibration map to fulfil the NOx emission constraint while minimising the fuel consumption. The calibration is adapted during a predefined time window based on the predicted engine performance on the estimated cycle and the difference between the actual and the constraint on engine NOx emissions. The method assessment was done experimentally in the engine test set-up. The engine performace using the method is compared with the state-of-the-art static calibration method for different NOx emission limits on real driving cycles. The online implementation of the method shows that the fuel consumption can be reduced by 3%-4% while staying within the emission limits, indicating that the estimation method is able to capture the main driving cycle characterstics.The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The authors acknowledge the support of Spanish Ministrrio de Economia, Industria y Competitivad through project TRA2016-78717-R.Luján, JM.; Pla Moreno, B.; Bares-Moreno, P.; Pandey, V. (2021). Adaptive calibration of Diesel engine injection for minimising fuel consumption with constrained NOx emissions in actual driving missions. International Journal of Engine Research. 22(6):1896-1905. https://doi.org/10.1177/1468087420918800S1896190522

Online Control of Automotive systems for improved Real-World Performance

[ES] La necesidad de mejorar el consumo de combustible y las emisiones de los sistemas propulsivos de automoción en condiciones reales de conducción es la base de esta tesis. Para ello, se exploran dos ejes: En primer lugar, el control de los sistemas de propulsión. El estado del arte de control en los sistemas propulsivos de automoción se basa en gran medida en el uso de técnicas de optimización que buscan las leyes de control que minimizan una función de coste en un conjunto de condiciones de operación denidas a priori. Estas leyes se almacenan en las ECUs de producción en forma de mapas de calibración de los diferentes actuadores del motor. Las incertidumbres asociadas al conjunto limitado de condiciones en el proceso de calibración dan lugar a un funcionamiento subóptimo del sistema de propulsión en condiciones de conducción real. Por lo tanto, en este trabajo se proponen métodos de control adaptativo que optimicen la gestión de la planta propulsiva a las condiciones esperadas de funcionamiento para un usuario y un caso determinado en lugar de a un conjunto genérico de condiciones. El segundo eje se reere a optimizar, en lugar de los parámetros de control del sistema propulsivo, la demanda de potencia de este, introduciendo al propio conductor en el bucle de control, sugiriéndole las acciones a tomar. En particular, este segundo eje se reere al control de la velocidad del vehículo (conocido popularmente como Eco-Driving en la literatura) en condiciones reales de conducción. Se proponen sistemas de aviso en tiempo real al conductor acerca de la velocidad óptima para minimizar el consumo del vehículo. Los métodos de control desarrollados para cada aplicación se describen en detalle en la tesis y se muestran ensayos experimentales de validación en los casos de estudio diseñados. Ambos ejes representan un problema de control óptimo, denido por un sistema dinámico, unas restricciones a cumplir y un coste a minimizar, en este sentido las herramientas desarrolladas en la tesis son comunes a los dos ejes: Un modelo de vehículo, una herramienta de predicción del ciclo de conducción y métodos de control óptimo (Programación Dinámica, Principio Mínimo de Pontryagin y Estrategia de Consumo Equivalente Mínimo). Dependiendo de la aplicación, los métodos desarrollados se implementaron en varios entornos experimentales: un motor térmico en sala de ensayos simulando el resto del vehículo, incluyendo el resto del sistema de propulsión híbrido y en un vehículo real. Los resultados muestran mejoras signicativas en el rendimiento del sistema de propulsión en términos de ahorro de combustible y emisiones en comparación con los métodos empleados en el estado del arte actual.[CA] La necessitat de millorar el consum de combustible i les emissions dels sistemes propulsius d'automoció en condicions reals de conducció és la base d'aquesta tesi. Per a això, s'exploren dos eixos: En primer lloc, el control dels sistemes de propulsió. L'estat de l'art de control en els sistemes propulsius d'automoció es basa en gran manera en l'ús de tècniques d'optimització que busquen les lleis de control que minimitzen una funció de cost en un conjunt de condicions d'operació denides a priori. Aquestes lleis s'emmagatzemen en les Ecus de producció en forma de mapes de calibratge dels diferents actuadors del motor. Les incerteses associades al conjunt limitat de condicions en el procés de calibratge donen lloc a un funcionament subòptim del sistema de propulsió en condicions de conducció real. Per tant, en aquest treball es proposen mètodes de control adaptatiu que optimitzen la gestió de la planta propulsiva a les condicions esperades de funcionament per a un usuari i un cas determinat en lloc d'un conjunt genèric de condicions. El segon eix es refereix a optimitzar, en lloc dels paràmetres de control del sistema propulsiu, la demanda de potència d'aquest, introduint al propi conductor en el bucle de control, suggerint-li les accions a prendre. En particular, aquest segon eix es refereix al control de la velocitat del vehicle (conegut popularment com Eco-*Driving en la literatura) en condicions reals de conducció. Es proposen sistemes d'avís en temps real al conductor sobre la velocitat òptima per a minimitzar el consum del vehicle. Els mètodes de control desenvolupats per a cada aplicació es descriuen detalladament en la tesi i es mostren assajos experimentals de validació en els casos d'estudi dissenyats. Tots dos eixos representen un problema de control òptim, denit per un sistema dinàmic, unes restriccions a complir i un cost a minimitzar, en aquest sentit les eines desenvolupades en la tesi són comunes als dos eixos: Un model de vehicle, una eina de predicció del cicle de conducció i mètodes de control òptim (Programació Dinàmica, Principi Mínim de *Pontryagin i Estratègia de Consum Equivalent Mínim). Depenent de l'aplicació, els mètodes desenvolupats es van implementar en diversos entorns experimentals: un motor tèrmic en sala d'assajos simulant la resta del vehicle, incloent la resta del sistema de propulsió híbrid i en un vehicle real. Els resultats mostren millores signicatives en el rendiment del sistema de propulsió en termes d'estalvi de combustible i emissions en comparació amb els mètodes emprats en l'estat de l'art actual.[EN] The need of improving the real-world fuel consumption and emission of automotive applications is the basis of this thesis. To this end, two verticals are explored: First is the online control of the powertrain systems. In state-of-the-art Optimal Control techniques (such as Dyanmic Programming, Pontryagins Minimum Principle, etc...) are extensively used to formulate the optimal control laws. These laws are stored in the production ECUs in the form of feedforward calibration maps. The unaccounted uncertainities related to the real-world during the powertrain calibration result in suboptimal operations of the powertrain in actual driving. Therefore, adaptive control methods are proposed in this work which, optimise the energy management of the conventional and the HEV powertrain control on real driving mission. The second vertical is regarding the vehicle speed control (popularly known as Eco-Driving in the literature) methods in real driving condition. In particular, speed advisory systems are proposed for real time application on a vehicle. The control methods developed for each application are described in details with their verication and validation on the designed case studies. Apart from the developed control methods, there are three tools that were developed and used at various stages of this thesis: A vehicle model, A driving cycle prediction tool and optimal control methods (dynamic programming, PMP and ECMS). Depending on the application, the developed methods were implemented on the Hardware-In-Loop Internal Combustion Engine testing setup or on a real vehicle. The results show signicant improvements in the performance of the powertrain in terms of fuel economy and emissions in comparison to the state-of-the-art methods.Pandey, V. (2021). Online Control of Automotive systems for improved Real-World Performance [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/173716TESI

Total pressure loss mechanism in a diesel engine turbocharger

Simulation tools are intensively used in the design stage of diesel engines due to their contributions to significant savings in cost and time for the engine development. Since most of DI diesel engines are turbocharged, it is of vital importance to hold a good understanding of turbine and compressor characteristic to predict the engine performance accurately. However, this data is often not available from turbocharger manufacturers, particularly for turbines. On available turbine maps the operating range of the turbine is constrained due to limitations of conventional turbocharger test benches. Operations with a wider range of turbocharger pressure ratios can be achieved by employing complex turbocharger test benches, which will also lead to higher costs including hardware and labour. An alternative solution is to develop numerical models for the turbocharger based on thermodynamics. In this thesis numerical models has been developed for predicting the performance of both the centrifugal compressors and turbines and they have been also validated using test cases, particularly for variable geometry turbines. Following detailed parametric studies, the turbocharger model has been validated against experimental data of a turbocharger with a variable geometry turbine. Results showed that the model was capable of predicting the characteristics maps of the turbocharger accurately, requiring a minimal amount of turbocharger geometric properties, experimental data and calibration parameters. Thus, by combing with the engine performance simulation software there is a highly potential for the numerical model developed in this work to become a useful tool for predicting engine performance and turbo matching calculations or diagnostic applications