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Recent work on thermo-electric (TE) systems has highlighted the need for refined heat transfer design as well as the long standing need for improved materials performance. Recent work on heat transfer for TE systems has shown that enhanced heat transfer is needed over and above what would normally be seen in a vehicle exhaust system. In particular a better understanding of flow development and boundary layer behaviour is needed to support new design proposals. In the meantime, recent work in TE materials suggests that with the use of skutterudites significant performance benefits can accrue over existing materials. The current generation of TE materials have non-dimensional thermoelectric figure of merit (ZT) values of around 1. Skutterudites have been demonstrated to have ZT values of about 1.4 and can maintain these values over a wider temperature range than do existing materials through the engineering of the TE device.

Selective Catalytic Reduction (SCR) is a leading aftertreatment 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.

This paper reports on an investigation into the potential for a thermoelectric generator (TEG) to improve the fuel economy of a mild hybrid vehicle. A simulation model of a parallel hybrid vehicle equipped with a TEG in the exhaust system is presented. This model is made up by three sub-models: a parallel hybrid vehicle model, an exhaust model and a TEG model. The model is based on a quasi-static approach, which runs a fast and simple estimation of the fuel consumption and CO2 emissions. The model is validated against both experimental and published data. Using this model, the annual fuel saving, CO2 reduction and net present value (NPV) of the TEG’s life time fuel saving are all investigated. The model is also used as a flexible tool for analysis of the sensitivity of vehicle fuel consumption to the TEG design parameters. The analysis results give an effective basis for optimization of the TEG design.

In modern powertrains systems, sensors are critical elements for advanced control. The identification of sensing requirements for such highly nonlinear systems is technically challenging. To support the sensor selection process, this paper proposes a methodology to quantify the information gained from sensors used to control nonlinear dynamic systems using a dynamic probabilistic framework. This builds on previous work to design a Bayesian observer to deal with nonlinear systems. This was applied to a bimodal model of the SCR aftertreatment system. Despite correctly observing the bimodal distribution of the internal Ammonia-NOx Ratio (ANR) state, it could not distinguish which state is the true state. This causes issues for a control engineer who is less interested in how precise a measurement is and more interested in the location within control parameter space. Information regarding the dynamics of the systems is required to resolve the bimodality.

Sensor selection for the control of modern powertrains is a recognised technical challenge. The key question is which set of sensors is best suited for an effective control strategy? This paper addresses the question through probabilistic modelling and Bayesian analysis. By quantifying uncertainties in the model, the propagation of sensor information throughout the model can be observed. The specific example is an abstract model of the slip behaviour of Selective Catalytic Reduction (SCR) DeNOx aftertreatment systems. Due to the ambiguity of the sensor reading, linearization-based approaches including the Extended Kalman Filter, or the Unscented Kalman Filter are not successful in resolving this problem. The stochastic literature suggests approximating these nonlinear distributions using methods such as Markov Chain Monte Carlo (MCMC), which is able in principle to resolve bimodal or multimodal results.

Selective catalytic reduction (SCR) has become the mainstream approach for removing heavy-duty (HD) diesel engine NOx emissions. Highly efficient SCR systems are a key enabling technology allowing engines to be calibrated for very high NOx output with a resultant gain in fuel consumption while still maintaining NOx emissions compliance. One key to the successful implementation of high efficiency SCR at elevated engine out NOx levels is the ability to introduce significantly more AdBlue into the exhaust flow while still ensuring complete ammonia production and avoiding the formation of deposits. This paper presents a body of experimental work conducted on an exhaust test bench using optical techniques including high-speed imaging and phase Doppler interferometry (PDI), applied under representative exhaust conditions to a HD diesel engine after-treatment system with optical access inside the mixer tube. Two different sprays were used to dose AdBlue onto the mixing device.

This research introduces a new, novel approach to reverse flow particulate filter regeneration enabled by rapidly pulsed electric discharges. The discharges physically dislodge particulate matter (PM) from the filter substrate and allow a very low reverse air flow to transport it to a soot handling system. The system is operable independent of filter temperature, does not expose the filter to high thermal stresses or temperatures, has no apparent upper limit for filter PM-mass level (regeneration of a filter up to 17 g/L has been demonstrated), and does not require any catalyst. The system is inherently scalable allowing application to monolithic filters of any size or shape and can be tailored to suit specific application requirements such as limits on maximum regeneration time or power consumption. For example a light duty application would require as little as 200-500W electrical power to regenerate a filter in less than ten minutes (i.e. passenger car GPF or DPF).

Modern thermal propulsion systems (TPS) as part of hybrid powertrains are becoming increasingly complex. They have an increased number of components in comparison to traditionally powered vehicles leading to increased demand in packaging requirements. Many of the components in these systems relate to achieving efficiency gains, weight saving and pollutant reduction. This includes turbochargers and diesel or gasoline particulate filters for example and these are known to be very sensitive to inlet boundary conditions. When overcoming packaging requirements, sub-optimal flow distributions throughout the TPS can easily occur. Moreover, the individual components are often designed in isolation assuming relatively flat and artificially quiescent inlet flow conditions in comparison to those they are actually presented with. Thus, some of the efficiency benefits are lost through reduced component aerodynamic efficiency.

This paper presents research into a novel autoselective electric discharge method for regenerating monolithic wall flow diesel particulate filters using low power over the entire range of temperatures and oxygen concentrations experienced within the exhaust systems of modern diesel engines. The ability to regenerate the filter independently of exhaust gas temperature and composition significantly reduces system complexity compared to other systems. In addition, the system does not require catalyst loading and uses only mass- produced electronic and electrical components, thus reducing the cost of the after-treatment package. Purpose built exhaust gas simulation test rigs were used to evaluate, develop and optimise the autoselective regeneration system. On-engine testing demonstrated the performance of the autoselective regeneration process under real engine conditions.

Hybrid technologies enable the reduction of noxious tailpipe emissions and conformance with ever-decreasing allowable homologation limits. The complexity of the hybrid powertrain technology leads to an energy management problem with multiple energy sinks and sources comprising the system resulting in a high-dimensional time dependent problem for which many solutions have been proposed. Methods that rely on accurate predictions of potential vehicle operations are demonstrably more optimal when compared to rule-based methodology [1]. In this paper, a previously proposed energy management strategy based on an offline optimization using dynamic programming is investigated. This is then coupled with an online model predictive control strategy to follow the predetermined optimal battery state of charge trajectory prescribed by the dynamic program.

Efficiency and durability are key areas of research and development in modern racing drivetrains. Stringent regulations necessitate the need for components capable of operating under highly loaded conditions whilst being efficient and reliable. Downsizing, increasing the power-to-weight ratio and modification of gear teeth geometry to reduce friction are some of the actions undertaken to achieve these objectives. These approaches can however result in reduced structural integrity and component durability. Achieving a balance between system reliability and optimal efficiency requires detailed integrated multidisciplinary analyses, with the consideration of system dynamics, contact mechanics/tribology and stress analysis/structural integrity. This paper presents an analytical model to predict quasi-static contact power losses in lubricated spur gear sets operating under the Elastohydrodynamic regime of lubrication.

A model-based urea-dosing controller has been developed for the selective catalytic reduction (SCR) units on a diesel engine exhaust aftertreatment system (EATS). The SCR units consist of an integrated SCR-coated filter and then followed by a flow-through SCR catalyst. The controller was developed based on an analysis of the data generated from a Millbrook London Transport Bus (MLTB) test cycle fed into a validated model of the SCR-filter and SCR units. The critical system parameters that showed strong correlation with outlet nitrogen oxides (NOx) and ammonia (NH3) emissions were first identified, and then the sensitivity of those parameters was analyzed. The most sensitive system parameters were configured as the controller gain parameters. A proportional controller based on the key parameters with optimized gains settings for the MLTB cycle delivered over a 10% reduction in cumulative NOx emission over the cycle compared to a fixed NH3/NOx ratio (ANR) controller.

Crankcase emissions are a complex mixture of combustion products and aerosol generated from lubrication oil. The crankcase emissions contribute substantially to the total particulate matter (PM) emitted from an engine. Environment legislation demands that either the combustion and crankcase emissions are combined to give a total measurement, or the crankcase gases are re-circulated back into the engine. There is a lack of understanding regarding the physical processes that generate crankcase aerosols, with a paucity of information on the size/mass concentrations of particles present in the crankcase. In this study the particulate matter crankcase emissions were measured from a fired and motored 4-cylinder compression ignition engine at a range of speeds and crankcase locations.

Variable valve actuation in heavy duty diesel engines is not well documented, because of diesel engine feature, such as, unthrottled air handling, which gives little room to improve pumping loss; a very high compression ratio, which makes the clearance between the piston and valve small at the top dead center. In order to avoid strike the piston while maximizing the valve movement scope, different strategies are adopted in this paper: (1) While exhaust valve closing is fixed, exhaust valve opening is changed; (2) While exhaust valve closing is fixed, late exhaust valve opening: (3) While inlet valve opening is fixed, inlet valve closing is changed; (4) Delayed Inlet valve and exhaust valve openings and closings; (5) Changing exhaust valve timing; (6) changing inlet valve timing; (7) Changing both inlet and exhaust timing, will be used.

Piston compression rings are thin, incomplete circular structures which are subject to complex motions during a typical 4-stroke internal combustion engine cycle. Ring dynamics comprises its inertial motion relative to the piston, within the confine of its seating groove. There are also elastodynamic modes, such as the ring in-plane motions. A number of modes can be excited, dependent on the net applied force. The latter includes the ring tension and cylinder pressure loading, both of which act outwards on the ring and conform it to the cylinder bore. There is also the radial inward force as the result of ring-bore conjunctional pressure (i.e. contact force). Under transient conditions, the inward and outward forces do not equilibrate, resulting in the small inertial radial motion of the ring.

The worldwide introduction of new emission standards and new, more encompassing, legislating cycles have led to a need to increase both a selective catalytic reduction (SCR) system’s capacity and conversion efficiency. To this end, it is important for an SCR system to operate to the extremes of its temperature range which in many systems is currently limited by the temperature at which diesel exhaust fluid (DEF) can easily decompose without the formation of deposits. This paper analyses a new system for low-temperature ammonia provision to the SCR reaction. Ammonia Creation and Conversion Technology (ACCT) uses pressure controlled thermal decomposition of DEF followed by re-formation to form a fluid with greater volatility and the same ammonia density as DEF conforming to ISO 22241. A dosing strategy can then be employed where any combination of DEF or ACCT solution can be used to provide ammonia as a reductant over the whole activity temperature range of a catalyst.

In recent years urea selective catalytic reduction (SCR) has become the principal method of NOx abatement within heavy duty (HD) diesel exhaust systems; however, with upcoming applications demanding NOx reduction efficiencies of above 96 % on engines producing upwards of 10 g·kWh−1 NOx, future diesel exhaust fluid (DEF) dosing systems will be required to operate stably at significantly increased dosing rates. Developing a dosing system capable of meeting the increased performance requirements demands an improved understanding of how DEF sprays interact with changing exhaust flows. This study has investigated four production systems representing a diverse range of dosing strategies in order to determine how performance is influenced by spray structure and identify promising strategies for further development. The construction of an optically accessible hot-air flow rig has enabled visualisation of DEF injection into flows representative of HD diesel exhaust conditions.

This paper presents a method to achieve a low order system model of the urea-based SCR catalyst coated filter (SCR-in-DPF or SCRF or SDPF), while preserving a high degree of fidelity. Proper orthogonal decomposition (POD), also known as principal component analysis (PCA), or Karhunen-Loéve decomposition (KLD), is a statistical method which achieves model order reduction by extracting the dominant characteristic modes of the system and devises a low-dimensional approximation on that basis. The motivation for using the POD approach is that the low-order model directly derives from the high-fidelity model (or experimental data) thereby retains the physics of the system. POD, with Galerkin projection, is applied to the 1D + 1D SCR-in-DPF model using ammonia surface coverage and wall temperature as the dominant system states to achieve model order reduction.