A crank-kinematics based engine cylinder pressure reconstruction model

A new inverse model is proposed for reconstructing steady-state and transient engine cylinder pressure using measured crank kinematics. An adaptive nonlinear time-dependent relationship is assumed between windowed-subsections of cylinder pressure and measured crank kinematics in a time-domain format (rather than in crank-angle-domain). This relationship comprises a linear sum of four separate nonlinear functions of crank jerk, acceleration, velocity, and crank angle. Each of these four nonlinear functions is obtained at each time instant by fitting separate m-term Chebychev polynomial expansions, where the total 4m instantaneous expansion coefficients are found using a standard (over-determined) linear least-square solution method. A convergence check on the calibration accuracy shows this initially improves as more Chebychev polynomial terms are used, but with further increase, the over-determined system becomes singular. Optimal accuracy Chebychev expansions are found to be of degree m=4, using 90 or more cycles of engine data to fit the model. To confirm the model accuracy in predictive mode, a defined measure is used, namely the ‘calibration peak pressure error’. This measure allows effective a priori exclusion of occasionally unacceptable predictions. The method is tested using varying speed data taken from a 3-cylinder DISI engine fitted with cylinder pressure sensors, and a high resolution shaft encoder. Using appropriately-filtered crank kinematics (plus the ‘calibration peak pressure error’), the model produces fast and accurate predictions for previously unseen data. Peak pressure predictions are consistently within 6.5% of target, whereas locations of peak pressure are consistently within ± 2.7˚ CA. The computational efficiency makes it very suitable for real-time implementation

A model-based control design approach for linear free-piston engines

A general design approach is presented for model-based control of piston position in a free-piston engine (FPE). The proposed approach controls either ‘bottom-dead-centre’ (BDC) or ‘top-dead-centre’ (TDC) position. The key advantage of the approach is that it facilitates controller parameter selection, by way of deriving parameter combinations that yield both stable BDC and stable TDC. Driving the piston motion towards a target compression ratio is therefore achieved with sound engineering insight, consequently allowing repeatable engine cycles for steady power output. The adopted control design approach is based on linear control-oriented models derived from exploitation of energy conservation principles in a two-stroke engine cycle. Two controllers are developed: A Proportional Integral (PI) controller with an associated stability condition expressed in terms of controller parameters, and a Linear Quadratic Regulator (LQR) to demonstrate a framework for advanced control design where needed. A detailed analysis is undertaken on two FPE case studies differing only by rebound device type, reporting simulation results for both PI and LQR control. The applicability of the proposed methodology to other common FPE configurations is examined to demonstrate its generality

A unified approach to engine cylinder pressure reconstruction using time-delay neural networks with crank kinematics or block vibration measurements

Closed-loop combustion control (CLCC) in gasoline engines can improve efficiency, calibration effort, and performance using different fuels. Knowledge of in-cylinder pressures is a key requirement for CLCC. Adaptive cylinder pressure reconstruction offers a realistic alternative to direct sensing, which is otherwise necessary as legislation requires continued reductions in CO2 and exhaust emissions. Direct sensing however is expensive and may not prove adequately robust. A new approach is developed for in-cylinder pressure reconstruction on gasoline engines. The approach uses Time-Delay feed-forward Artificial Neural Networks trained with the standard Levenberg-Marquardt algorithm. The same approach can be applied to reconstruction via measured crank kinematics obtained from a shaft encoder, or measured engine cylinder block vibrations obtained from a production knock sensor. The basis of the procedure is initially justified by examination of the information content within measured data, which is considered to be equally important as the network architecture and training methodology. Key hypotheses are constructed and tested using data taken from a 3-cylinder (DISI) engine to reveal the influence of the data information content on reconstruction potential. The findings of these hypotheses tests are then used to develop the methodology. The approach is tested by reconstructing cylinder pressure across a wide range of steady-state engine operation using both measured crank kinematics and block accelerations. The results obtained show a very marked improvement over previously published reconstruction accuracy for both crank kinematics and cylinder block vibration based reconstruction using measurements obtained from a multi-cylinder engine. The paper shows that by careful processing of measured engine data, a standard neural network architecture and a standard training algorithm can be used to very accurately reconstruct engine cylinder pressure with high levels of robustness and efficiency

Infrastructural Speculations: Tactics for Designing and Interrogating Lifeworlds

This paper introduces “infrastructural speculations,” an orientation toward speculative design that considers the complex and long-lived relationships of technologies with broader systems, beyond moments of immediate invention and design. As modes of speculation are increasingly used to interrogate questions of broad societal concern, it is pertinent to develop an orientation that foregrounds the “lifeworld” of artifacts—the social, perceptual, and political environment in which they exist. While speculative designs often imply a lifeworld, infrastructural speculations place lifeworlds at the center of design concern, calling attention to the cultural, regulatory, environmental, and repair conditions that enable and surround particular future visions. By articulating connections and affinities between speculative design and infrastructure studies research, we contribute a set of design tactics for producing infrastructural speculations. These tactics help design researchers interrogate the complex and ongoing entanglements among technologies, institutions, practices, and systems of power when gauging the stakes of alternate lifeworlds

A review of evaporative cooling system concepts for engine thermal management in motor vehicles

Evaporative cooling system concepts proposed over the past century for engine thermal management in automotive applications are examined and critically reviewed. The purpose of the review is to establish evident system shortcomings and to identify remaining research questions that need to be addressed to enable this important technology to be adopted by vehicle manufacturers. Initially, the benefits of evaporative cooling systems are restated in terms of improved engine efficiency, reduced CO2 emissions, and improved fuel economy. An historical coverage follows of the proposed concepts dating back to 1918. Possible evaporative cooling concepts are then classified into four distinct classes and critically reviewed. This culminates in an assessment of the available evidence to establish the reasons why no system has yet made it to serial production. Then, by systematic examination of the critical areas in evaporative cooling systems for application to automotive engine cooling, remaining research challenges are identified

Conjugate heat transfer predictions for subcooled boiling flow in a horizontal channel using a volume-of-fluid framework.

The accuracy of CFD-based heat transfer predictions have been examined of relevance to liquid cooling of IC engines at high engine loads where some nucleate boiling occurs. Predictions based on: i) the Reynolds Averaged Navier-Stokes (RANS) solution, and ii) Large Eddy Simulation (LES), have been generated. The purpose of these simulations is to establish the role of turbulence modelling on the accuracy and efficiency of heat transfer predictions for engine-like thermal conditions where published experimental data is available. A multi-phase mixture modelling approach, with a Volume-of-Fluid interface-capturing method, has been employed. To predict heat transfer in the boiling regime, the empirical boiling correlation of Rohsenow is used for both RANS and LES. The rate of vapour-mass generation at the wall surface is determined from the heat flux associated with the evaporation phase change. Predictions via CFD are compared with published experimental data showing that LES gives only slightly more accurate temperature predictions compared to RANS but at substantially higher computational cost.N/

Expanding modes of reflection in design futuring

Design futuring approaches, such as speculative design, design fiction and others, seek to (re)envision futures and explore alternatives. As design futuring becomes established in HCI design research, there is an opportunity to expand and develop these approaches. To that end, by reflecting on our own research and examining related work, we contribute five modes of reflection. These modes concern formgiving, temporality, researcher positionality, real-world engagement, and knowledge production. We illustrate the value of each mode through careful analysis of selected design exemplars and provide questions to interrogate the practice of design futuring. Each reflective mode offers productive resources for design practitioners and researchers to articulate their work, generate new directions for their work, and analyze their own and others’ work.

Making Sense of Blockchain Applications:A Typology for HCI

Blockchain is an emerging infrastructural technology that is proposed to fundamentally transform the ways in which people transact, trust, collaborate, organize and identify themselves. In this paper, we construct a typology of emerging blockchain applications, consider the domains in which they are applied, and identify distinguishing features of this new technology. We argue that there is a unique role for the HCI community in linking the design and application of blockchain technology towards lived experience and the articulation of human values. In particular, we note how the accounting of transactions, a trust in immutable code and algorithms, and the leveraging of distributed crowds and publics around vast interoperable databases all relate to longstanding issues of importance for the field. We conclude by highlighting core conceptual and methodological challenges for HCI researchers beginning to work with blockchain and distributed ledger technologies