Search Results

The TC48 project is developing a state-of-the-art, exceptionally low cost, 48V Plug-in hybrid electric (PHEV) demonstration drivetrain suitable for electrically powered urban driving, hybrid operation, and internal combustion engine powered high speed motoring. This paper explains the motivation for the project, and presents the layout options considered and the rationale by which these were reduced. The vehicle simulation model used to evaluate the layout options is described and discussed. The modelling work was used in order to support and justify the design choices made. The design of the vehicle's control systems is discussed, presenting simulation results. The physical embodiment of the design is not reported in this paper. The paper describes analysis of small vehicles in the marketplace, including aspects of range and cost, leading to the justification for the specification of the TC48 system.

Particulate number (PN) standards in the current ‘Euro 6’ European emissions standards pose a challenge for engine designers and calibrators during the warm-up phases of cold direct injection spark ignition (DISI) engines. To achieve catalyst light-off in the shortest time, engine strategies are often employed which inherently use more fuel to attain higher exhaust temperatures. This can lead to the generation of locally fuel-rich regions within the combustion chamber and the emission of particulates. This investigation analyses the combustion structures during the transient start-up phase of an optical DISI engine. High-speed, colour 9 kHz imaging was used to investigate five important operating points of an engine start-up strategy whilst simultaneously recording in-cylinder pressure.

For a spark-ignition engine, the parasitic loss suffered as a result of conventional throttling has long been recognised as a major reason for poor part-load fuel efficiency. While lean, stratified charge, operation addresses this issue, exhaust gas aftertreatment is more challenging compared with homogeneous operation and three-way catalyst after-treatment. This paper adopts a different approach: homogeneous charge direct injection (DI) operation with variable valve actuations which reduce throttling losses. In particular, low-lift and early inlet valve closing (EIVC) strategies are investigated. Results from a thermodynamic single cylinder engine are presented that quantify the effect of two low-lift camshafts and one standard high-lift camshaft operating EIVC strategies at four engine running conditions; both, two- and single-inlet valve operation were investigated. Tests were conducted for both port and DI fuelling, under stoichiometric conditions.

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.

As lithium-ion electric vehicle (EV) batteries are sensitive to the conditions they are exposed to during charging and discharging, operational control has been an important research area. While an understanding of the effects current load and operation temperature has on the ageing stability of a battery has been established, associated control strategies are yet to be fully optimized. Most battery charging studies utilize controlled ambient temperatures and basic defined cycles, which may only apply to a small subset of real-world EV consumers. This leads to control strategies that do not consider electrical grid price fluctuation, user driving habits or local weather conditions. This paper looks to propose improved smart charging strategies of EVs to reduce consumer costs while also increasing the battery longevity. To accomplish the primary objective, A model has been generated that simulates the standard charge cycle of a battery.

In 2012 MAHLE Powertrain developed a range-extended electric vehicle (REEV) demonstrator, based on a series hybrid configuration, and uses a battery to store electrical energy from the grid. Once the battery state of charge (SOC) is depleted a gasoline engine (range extender) is activated to provide the energy required to propel the vehicle. As part of the continuing development of this vehicle, MAHLE Powertrain has developed control software which can intelligently manage the use of the battery energy through the combined use of GPS and road topographical data. Advanced knowledge of the route prior to the start of a journey enables the software to calculate the SOC throughout the journey and pre-determine the optimum operating strategy for the range extender to enable best charging efficiency and minimize NVH. The software can also operate without a pre-determined route being selected.

On future UAVs it is envisaged that the power requirements of all on-board electrical systems will increase. In most flight (mission) situations the installed power generation will have adequate capacity to operate the aircraft. It is possible that during abnormal situations such as coolant blockage the generators on-board may be forced to operate under very high load conditions. The main failure mechanism for a generator is overheating and subsequent disintegration of windings, hence the research problem being addressed here is to manage the loads upon the generator to prevent overheats. The research presented here summarizes the modeling of the generator and formation of the load management system. Results are presented showing the system reallocating loads after a fault during flight, preventing overheat of the generators and successfully completing the mission.

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).

Powertrain thermal encapsulation has the potential to improve fuel consumption and CO2 via heat retention. Heat retained within the powertrain after a period of engine-off, can increase the temperature of the next engine start hours after key-off. This in turn reduces inefficiencies associated with sub-optimal temperatures such as friction. The Ambient Temperature Correction Test was adopted in the current work which contains two World-wide harmonised Light duty Test Procedure (WLTP) cycles separated by a 9-hour soak period. A coupled 1D - 3D computational approach was used to capture heat retention characteristics and subsequent warm-up effects. A 1-D powertrain warm-up model was developed in GT-Suite to capture the thermal warm-up characteristics of the powertrain. The model included a temperature dependent friction model, the thermal-hydraulic characteristics of the cooling and lubrication circuits as well as parasitic losses associated with pumps.

Considerable engineering effort is now being applied to the design and development of Soapboxes entered in the Goodwood Festival of Speed Gravity Challenge. With average speeds of 18 ms-1 (40 mph) from a standing start along the 0.7 mile course and maximum speeds of around 27 ms-1 (60 mph), the aerodynamic contribution to performance is significant. This paper discusses the aerodynamic considerations given to the design of the leading Soapboxes and to the racing conditions experienced. Analysis and test techniques which may also be employed are also described.

On future Unmanned Air Vehicles (UAVs) it is envisaged that the power requirements of all on-board electrical systems will increase. Whilst, in most flight (mission) situations the installed generation capacity will have adequate capacity to operate the systems, it is possible that during certain abnormal situations the generators on-board may be forced to operate under very high load conditions. The main failure mechanism for a generator is overheating and subsequent disintegration of windings, hence the research problem being addressed here is that of modelling the thermal dynamics of a generator in such a way that the model can be used to predict future temperatures given knowledge of the future mission requirements. The temperature predictions will be used to allow prioritising of the mission actions in order to allow maximum utilisation of power generation capacity without overheating.

The performance of energy flow management strategies is essential for the success of hybrid electric vehicles (HEVs), which are considered amongst the most promising solutions for improving fuel economy as well as reducing exhaust emissions. The heavy duty HEVs engaged in cycles characterized by start-stop configuration has attracted widely interests, especially in off-road applications. In this paper, a fuzzy equivalent consumption minimization strategy (F-ECMS) is proposed as an intelligent real-time energy management solution for heavy duty HEVs. The online optimization problem is formulated as minimizing a cost function, in terms of weighted fuel power and electrical power. A fuzzy rule-based approach is applied on the weight tuning within the cost function, with respect to the variations of the battery state-of-charge (SOC) and elapsed time.