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The car buying public’s enthusiasm for electric vehicles continues to accelerate rapidly, driven by a desire to fulfil global climate change objectives, and supported by tax incentives. However, range anxiety persists as one of the main barriers to take-up, because larger battery packs remain heavy and expensive (cell price reductions are slowing). One way to mitigate these disadvantages is to fit a range extender system, powered by an efficient internal combustion engine, but such systems can cause noise concerns. Ricardo has developed a simulation-based approach, pragmatically applicable at concept stage, to define the range extender operating conditions that minimize the impact on noise heard by the driver and passengers inside the vehicle. Transfer path analysis considered both air-borne and structure-borne noise contributions from the range extender, in context with noise contributions from electric drive unit, road and wind, under various typical vehicle operating conditions.

Models of hybrid powertrains are used to establish the best combination of conventional engine power and electric motor power for the current driving situation. The model is characteristic for having two control inputs and one output constraint: the total torque should be equal to the torque requested by the driver. To eliminate the constraint, several alternative formulations are used, considering engine power or motor power or even the ratio between them as a single control input. From this input and the constraint, both power levels can be deduced. There are different popular choices for this one control input. This paper presents a novel model based on an input linearizing transformation. It is demonstrably superior to alternative model forms, in that the core dynamics of the model (battery state of energy) are linear, and the non-linearities of the model are pushed into the inputs and outputs in a Wiener/Hammerstein form.

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.

Vehicle emissions and fuel economy in real-world driving conditions are currently under considerable scrutiny. Key to achieving optimum performance for a given hardware set and control scheme is a calibration that optimizes controller gains such that inputs are scheduled over the operating space to minimize emissions and maximize fuel economy. Generating a suitable calibration requires data that is both precise and accurate, this data is used to generate models that are deployed as part of the calibration optimization process. This paper evaluates the repeatability of typical steady-state measurements used for calibration of engine controllers that will ultimately determine vehicle level emissions for homologation include Real Driving Emissions (RDE). Stabilization requirements as indicated by three different measurements are evaluated and shown to be different within the same experiment, depending on the metric used.

Proton exchange membrane fuel cell (PEMFC) provides a promising future low carbon automotive powertrain solution. The catalyst layer (CL) is its core component which directly influences the output performance. PEMFC performance can be greatly improved by the effective optimization of CL composition. This work demonstrates a deep optimization of CL composition for improving the PEMFC performance, including the platinum (Pt) loading, Pt percentage of carbon-supported Pt and ionomer to carbon ratio of the anode and the cathode,. The simulation results by a PEMFC three-dimensional (3D) computation fluid dynamics (CFD) model coupled with the CL agglomerate model is used to train the artificial neural network (ANN) which can efficiently predict the current density under different CL composition. Squared correlation coefficient (R-square) and mean percentage error in the training set and validation set are 0.9867, 0.2635% and 0.9543, 1.1275%, respectively.

Global automotive fuel economy and emissions pressures mean that 48 V hybridisation will become a significant presence in the passenger car market. The complexity of powertrain solutions is increasing in order to further improve fuel economy for hybrid vehicles and maintain robust emissions performance. However, this results in complex interactions between technologies which are difficult to identify through traditional development approaches, resulting in sub-optimal solutions for either vehicle attributes or cost. The results presented in this paper are from a simulation programme focussed on the optimisation of various advanced powertrain technologies on 48 V hybrid vehicle platforms. The technologies assessed include an electrically heated catalyst, an insulated turbocharger, an electric water pump and a thermal management module.

Many modern I.C. engines rely on some form of active control of injection, timing and/or ignition timing to help combat tailpipe out emissions, increase the fuel economy and improve engine drivability. However, development of these strategies is often optimised to suit the average cycle at each condition; an assumption that can lead to sub-optimal performance, especially an increase in particulate (PN) emissions as I.C. engine operation, and in-particular its charge motion is subject to cycle-to-cycle variation (CCV). Literature shows that the locations of otherwise repeatable large-scale flow structures may vary by as much 25% of the bore dimension; this could have an impact on fuel break-up and distribution and therefore subsequent combustion performance and emissions.

This paper presents a novel approach to augment existing engine calibrations to deliver improved engine performance during a transient, through the application of multi-objective optimization techniques to the calibration of the Variable Valve Timing (VVT) system of a 1.0 litre gasoline engine. Current mature calibration approaches for the VVT system are predominantly based on steady state techniques which fail to consider the engine dynamic behaviour in real world driving, which is heavily transient. In this study the total integrated fuel consumption and engine-out NOx emissions over a 2-minute segment of the transient Worldwide Light-duty Test Cycle are minimised in a constrained multi-objective optimisation framework to achieve an updated calibration for the VVT control. The cycle segment was identified as an area with high NOx emissions.

With the increasing stringent emissions legislation on ICEs, alongside requirements for enhanced fuel efficiency as key driving factors for many OEMs, there are many research activities supported by the automotive industry that focus on the development of hybrid and pure EVs. This change in direction from engine downsizing to the use of electric motors presents many new challenges concerning NVH performance, durability and component life. This paper presents the development of experimental methodology into the measurement of NVH characteristics in these new powertrains, thus characterizing the structure borne noise transmissibility through the shaft and the bearing to the housing. A feasibility study and design of a new system level test rig have been conducted to allow for sinusoidal radial loading of the shaft, which is synchronized with the shaft’s rotary frequency under high-speed transient conditions in order to evaluate the phenomena in the system.

The drag coefficient at zero yaw angle is the single parameter usually used to define the aerodynamic drag characteristics of a passenger car. However, this is usually the minimum drag condition and will, for example, lead to an underestimate of the effect of aerodynamic drag on fuel consumption because the important influence of the natural wind has been excluded. An alternative measure of aerodynamic drag should take into account the effect of nonzero yaw angles and a variant of wind-averaged drag is suggested as the best option. A wind-averaged drag coefficient (CDW) is usually derived for a particular vehicle speed using a representative wind speed distribution. In the particular case where the road speed distribution is specified, as for a drive cycle to determine fuel economy, a relevant drag coefficient can be derived by using a weighted road speed.

Cars in several motor sports series, such as Formula 1, make use of multi-element front wings to provide downforce. These wings also provide onset flows to other surfaces that generate downforce. These elements are highly loaded to maximise their performance and are generally operating close to stall. Rubber debris, often known as marbles, created from the high slip experienced by the soft compound tyres can become lodged in the multiple elements of a front wing. This will lead to a reduction in the effectiveness of the wing over the course of a race. This work will study the effect of such debris, both experimentally and numerically, on an inverted double element wing in ground effect at representative Reynolds numbers. The wing was mounted at two different ride heights above a fixed false-floor in the Loughborough University wind tunnel and the effect of debris blockage modelled by closing sections of the gap between elements with tape.

This literature review considers the problem of finding a suitable configuration of sensors and actuators for the control of an internal combustion engine. It takes a look at the methods, algorithms, processes, metrics, applications, research groups and patents relevant for this topic. Several formal metric have been proposed, but practical use remains limited. Maximal information criteria are theoretically optimal for selecting sensors, but hard to apply to a system as complex and nonlinear as an engine. Thus, we reviewed methods applied to neighboring fields including nonlinear systems and non-minimal phase systems. Furthermore, the closed loop nature of control means that information is not the only consideration, and speed, stability and robustness have to be considered. The optimal use of sensor information also requires the use of models, observers, state estimators or virtual sensors, and practical acceptance of these remains limited.

Thermoelectric generator has very quickly become a hot research topic in the last five years because its broad application area and very attractive features such as no moving parts, low maintenance, variety of thermoelectric materials that total together cover a wide temperature range. The biggest disadvantage of the thermoelectric generator is its low conversion efficiency. So that when design and manufacture a thermoelectric generator for exhaust waste heat recovery from an automotive engine, the benefit of fuel consumption from applying a thermoelectric generator would be very sensitive to the weight, the dimensions, the cost and the practical conversion efficiency. Additionally, the exhaust gas conditions vary with the change of engine operating point. This creates a big challenge for the design of the hot side heat exchanger in terms of optimizing the electrical output of the thermoelectric generator during an engine transient cycle.

Sports Utility Vehicles (SUVs) often have blunt rear end geometries for design and practicality, which is not typically aerodynamic. Drag can be reduced with a number of passive and active methods, which are generally prioritised at zero yaw, which is not entirely representative of the “on road” environment. As such, to combine a visually square geometry (at rest) with optimal drag reductions at non-zero yaw, an adaptive system that applies vertical side edge tapers independently is tested statically. A parametric study has been undertaken in Loughborough University’s Large Wind Tunnel with the ¼ scale Windsor Model. The aerodynamic effect of implementing asymmetric side tapering has been assessed for a range of yaw angles (0°, ±2.5°, ±5° and ±10°) on the force and moment coefficients.

Clutches are commonly utilised in passenger type and off-road heavy-duty vehicles to disconnect the engine from the driveline and other parasitic loads. In off-road heavy-duty vehicles, along with fuel efficiency start-up functionality at extended ambient conditions, such as low temperature and intake absolute pressure are crucial. Off-road vehicle manufacturers can overcome the parasitic loads in these conditions by oversizing the engine. Caterpillar Inc. as the pioneer in off-road technology has developed a novel clutch design to allow for engine downsizing while vehicle’s performance is not affected. The tribological behaviour of the clutch will be crucial to start engagement promptly and reach the maximum clutch capacity in the shortest possible time and smoothest way in terms of dynamics. A multi-body dynamics model of the clutch system is developed in MSC ADAMS. The flywheel is introducing the same speed and torque as the engine (represents the engine input to the clutch).

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.

The application of state-of-art thermoelectric generator (TEG) in automotive engine has potential to reduce more than 2% fuel consumption and hence the CO2 emissions. This figure is expected to be increased to 5%~10% in the near future when new thermoelectric material with higher properties is fabricated. However, in order to maximize the TEG output power, there are a few issues need to be considered in the design stage such as the number of modules, the connection of modules, the geometry of the thermoelectric module, the DC-DC converter circuit, the geometry of the heat exchanger especially the hot side heat exchanger etc. These issues can only be investigated via a proper TEG model. The authors introduced four ways of TEG modelling which in the increasing complexity order are MATLB function based model, MATLAB Simscape based Simulink model, GT-power TEG model and CFD STAR-CCM+ model. Both Simscape model and GT-Power model have intrinsic dynamic model performance.

Thermoelectric generator (TEG) has received more and more attention in its application in the harvesting of waste thermal energy in automotive engines. Even though the commercial Bismuth Telluride thermoelectric material only have 5% efficiency and 250°C hot side temperature limit, it is possible to generate peak 1kW electrical energy from a heavy-duty engine. If being equipped with 500W TEG, a passenger car has potential to save more than 2% fuel consumption and hence CO2 emission reduction. TEG has advantages of compact and motionless parts over other thermal harvest technologies such as Organic Rankine Cycle (ORC) and Turbo-Compound (TC). Intense research works are being carried on improving the thermal efficiency of the thermoelectric materials and increasing the hot side temperature limit. Future thermoelectric modules are expected to have 10% to 20% efficiency and over 500°C hot side temperature limit.

This paper surveys publications on automotive powertrain control, relating to modern GTDI (Gasoline Turbocharged Direct Injection) engines. The requirements for gasoline engines are optimising the airpath but future legislation suggests not only a finely controlled airpath but also some level of electrification. Fundamentals of controls modelling are revisited and advancements are highlighted. In particular, a modern GTDI airpath is presented based on basic building blocks (volumes, turbocharger, throttle, valves and variable cam timing or VCT) with an example of a system interaction, based on boost pressure and lambda control. Further, an advanced airpath could be considered with applications to downsizing and fuel economy. A further electrification step is reviewed which involves interactions with the airpath and requires a robust energy management strategy. Examples are taken of energy recovery and e-machine placement.

The goal of grid friendly charging is to avoid putting additional load on the electricity grid when it is heavily loaded already, and to reduce the cost of charging to the consumer. In a smart metering system, Day Ahead tariff (DA) prices are announced in advance for the next day. This information can be used for a simple optimization control, to select to charge at cheapest times. However, the balance of supply and demand is not fully known in advance and the Real-Time Prices (RTP) are therefore likely to be different at times. There is always a risk of a sudden price change, hence adding a stochastic element to the optimization in turn requiring dynamic control to achieve optimal time selection. A stochastic dynamic program (SDP) controller which takes this problem into account has been made and proven by simulation in a previous paper.