New regulations on pollutants and, specially, on CO2 emissions could restrict the use of the internal combustion engine in automotive applications. This paper presents a review of different technologies under development for meeting such regulations, ranging from new combustion concepts to advanced boosting methods and after-treatment systems. Many of them need an accurate control of the operating conditions and, in many cases, they impose demanding requirements at a system integration level. In this framework, engine control disciplines will be key for the implementation and development of the next generation engines, taking profit of recent advancements in models, methods and sensors. According to authors’ opinion, the internal combustion engine will still be the dominant technology in automotive applications for the next decades.

/pdf/a-challenging-future-for-the-ic-engine-new-technologies-and-27pil1kml9.pdf

A Challenging Future for the IC Engine: New Technologies and the Control Role

The development history of automotive engineering has shown the essential role of transmissions in road vehicles primarily powered by internal combustion engines. The engine with its physical constraints on the torque and speed requires a transmission to have its power converted to the drive power demand at the vehicle wheels. Under dynamic driving conditions, the transmission is required to shift in order to match the engine power with the changing drive power. Furthermore, a gear shift decision is expected to be consistent such that vehicle can remain in the next gear for a period of time without deteriorating the acceleration capability. Therefore, an optimal conversion of the engine power plays a key role in improving the fuel economy and driveability. Moreover, the consequences of the assumptions related to the discrete state variable-dependent losses, e.g. gear shifting, clutch slippage and engine starting, and their e?ect on the gear shift control strategy are necessary to be analyzed to yield insights into the fuel usage. The ?rst part of the thesis deals with the design of gear shift strategies for electronically controlled discrete ratio transmissions used in both conventional vehicles and Hybrid Electric Vehicles (HEVs). For conventional vehicles, together with the fuel economy, the driveability is systematically addressed in a Dynamic Programming (DP) based optimal gear shift strategy by three methods: i) the weighted inverse of the power re¬serve, ii) the constant power reserve, and iii) the variable power reserve. In addition, a Stochastic Dynamic Programming (SDP) algorithm is utilized to optimize the gear shift strategy, subject to a stochastic distribution of the power request, in order to minimize the expected fuel consumption over an in?nite horizon. Hence, the SDP-based gear shift strategy intrinsically respects the driveability and is realtime implementable. By per¬forming a comparative analysis of all proposed gear shift methods, it is shown that the variable power reserve method achieves the highest fuel economy without deteriorating the driveability. Moreover, for HEVs, a novel fuel-optimal control algorithm, consist-ing of the continuous power split and discrete gear shift, engine on-o? problems, based on a combination of DP and Pontryagin’s Minimum Principle (PMP) is developed for the corresponding hybrid dynamical system. This so-called DP-PMP gear shift control approach benchmarks the development of an online implementable control strategy in terms of the optimal tradeo? between calculation accuracy and computational e?ciency. Driven by an ultimate goal of realizing an online gear shift strategy, a gear shift map design methodology for discrete ratio transmissions is developed, which is applied for both conventional vehicles and HEVs. The design methodology uses an optimal gear shift algorithm as a basis to derive the optimal gear shift patterns. Accordingly, statis¬tical theory is applied to analyze the optimal gear shift pattern in order to extract the time-invariant shift rules. This alternative two-step design procedure makes the gear shift map: i) respect the fuel economy and driveability, ii) be consistent and robust with respect to shift busyness, and iii) be realtime implementation. The design process is ?exible and time e?cient such that an applicability to various powertrain systems con?gured with discrete ratio transmissions is possible. Furthermore, the study in this thesis addresses the trend of utilizing the route information in the powertrain control system by proposing an integrated predictive gear shift strategy concept, consisting of a velocity algorithm and a predictive algorithm. The velocity algorithm improves the fuel economy in simulation considerably by proposing a fuel-optimal velocity trajectory over a certain driving horizon for the vehicle to follow. The predictive algorithm suc¬cessfully utilizes a prede?ned velocity pro?le over a certain horizon in order to realize a fuel economy improvement very close to that of the globally optimal algorithm (DP). In the second part of the thesis, the energetic losses, involved with the gear shift and engine start events in an automated manual transmission-based HEV, are modeled. The e?ect of these losses on the control strategies and fuel consumption for (non-)powershift transmission technologies is investigated. Regarding the gear shift loss, the study ?rstly ever discloses a perception of a fuel-e?cient advantage of the powershift transmissions over the non-powershift ones applied for commercial vehicles. It is also shown that the engine start loss can not be ignored in seeking for a fair evaluation of the fuel economy. Moreover, the sensitivity study of the fuel consumption with respect to the prediction horizon reveals that a predictive energy management strategy can realize the highest achievable fuel economy with a horizon of a few seconds ahead. The last part of the thesis focuses on investigating the sensitivity of an optimal gear shift strategy to the relevant control design objectives, i.e. fuel economy, driveability and comfort. A singu¬lar value decomposition based method is introduced to analyze the possible correlations and interdependencies among the design objectives. This allows that some of the pos¬sible dependent design objective(s) can be removed from the objective function of the corresponding optimal control problem, hence thereby reducing the design complexity.

/pdf/gear-shift-strategies-for-automotive-transmissions-2agdybw4y9.pdf

Gear shift strategies for automotive transmissions

Robust Filtering for Ammonia Coverage Estimation in Diesel Engine Selective Catalytic Reduction Systems

Selective Catalytic Reduction (SCR) is a leading after treatment technology for the removal of nitrogen oxide (NOx) from exhaust gases (DeNOx). It presents an interesting control challenge, especially at high conversion, because both reagents (NOx and ammonia) are toxic, and therefore an excess of either is highly undesirable. Numerous system layouts and control methods have been developed for SCR systems, driven by the need to meet future emission standards. This paper summarizes the current state-of-the-art control methods for the SCR aftertreatment systems, and provides a structured and comprehensive overview of the research on SCR control. The existing control techniques fall into three main categories: traditional SCR control methods, model-based SCR control methods, and advanced SCR control methods. For each category, the basic control technique is defined. Further techniques in the same category are then explained and appreciated for their relative advantages and disadvantages. Thus this paper presents a snapshot of the current state of the art for the research area of SCR control. This is a very active field, and it is hoped that by providing a better understanding of the different control strategies already developed for SCR control, future areas of interest will be identified and developed with the ultimate aim of satisfying the increasingly stringent emissions legislation. Copyright © 2014 SAE International.

/pdf/the-state-of-the-art-in-selective-catalytic-reduction-j27ks8i09k.pdf

The State of the Art in Selective Catalytic Reduction Control

Supervisory control of a heavy-duty diesel engine with an electrified waste heat recovery system

Selective catalytic reduction (SCR) is a promising diesel after treatment technology that enables low nitrogen oxides (NOx) tailpipe emissions with relatively low fuel consumption. Future emission legislation is pushing the boundaries for SCR control systems to achieve high NOx conversion within a tailpipe ammonia (NH3) slip constraint, and to provide robustness to meet in-use compliance requirements. This work presents a new adaptive control strategy that uses an ammonia feedback sensor and an online ammonia storage model. Experimental validation on a 12-liter heavy-duty diesel engine with a 34-liter Zeolite SCR catalyst shows good performance and robustness against urea under- and over-dosage for both the European steady-state and transient test cycles. The new strategy is compared with a NOx sensor-based control strategy with cross-sensitivity compensation. It proved to be superior in terms of transient adaptation and taking an NH3 slip constraint into account.

/pdf/experimental-demonstration-of-a-new-model-based-scr-control-59mswyke92.pdf

Experimental Demonstration of a New Model-Based SCR Control Strategy for Cleaner Heavy-Duty Diesel Engines

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Experimental Demonstration of a New Model-Based SCR Control Strategy for Cleaner Heavy-Duty Diesel Engines