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Energy management strategies greatly influence the power performance and fuel economy of series hybrid electric tracked bulldozers. In this paper, we present a procedure for the design of a power management strategy by defining a cost function, in this case, the minimization of the vehicle’s fuel consumption over a driving cycle. To explore the fuel-saving potential of a series hybrid electric tracked bulldozer, a dynamic programming (DP) algorithm is utilized to determine the optimal control actions for a series hybrid powertrain, and this can be the benchmark for the assessment of other control strategies. The results from comparing the DP strategy and the rule-based control strategy indicate that this procedure results in approximately a 7% improvement in fuel economy.

The purpose of this study is to present a parametric fuel tank filling model from first principles. The aim is to build a tool that can help with the initial tank layout, to make sure the design does not promote premature shut off. The governing equations of the model are detailed and results for a test case are presented. The model is based on a common set of parameters enabling it to be adapted to a set of design constrains. Additionally, the model is validated by experimental data where available and a sensitivity analysis on critical design parameters that promote premature shut off is performed.

Motorcycle models in the literature are derived using the Lagrangian formulation approach and are generally complex in order to satisfy the requirement for accuracy of the response. The objective of this paper is to develop a simplified motorcycle model, which although reduced in complexity, captures fundamental dynamic behavior. The resulting model will have two main uses. The first use will be as an explanatory aid to introduce engineers to the dynamics of motorcycles. The second application for the motorcycle model developed in this paper is for incorporation in active bike control stability systems. This is a subtly different objective to models required for simulation only where accuracy of the response is of paramount importance. The same motorcycle model concepts will be used in the paper to develop both a transient non-linear and linearised steady state model.

Navier-Stokes calculations for the flow around an isolated wheel have been performed. Both a stationary wheel on a fixed ground and a rotating wheel on a moving ground were considered. Extensive comparisons with experimental measurements of surface static pressure coefficient and wake total pressure are made. These show that CFD can give good qualitative results for the flow field around both stationary and rotating wheels. Highlighted are details about the separation process from the top of the wheel and the flow structure around the wheel contact area.

In a multi-pass weld, the development of residual stress to a large extent depends on the response of the weld metal, heat affected zone and parent material to complex thermo-mechanical cycles during welding. Previous investigations on this subject mostly focused on mechanical tensioning or heat treatment to modify the residual stress distribution in and around the weld. In this research, microstructural refinement with modification of residual stress state was attempted by applying post weld cold rolling followed by laser processing. The hardening of the weld metal was evaluated after welding, post weld cold rolling and post weld cold rolling followed by laser processing. The residual stress was determined non-destructively by using neutron diffraction. Hardness results showed evidence of plastic deformation up to 4 mm below the weld surface.

The flow field and body aerodynamic loads on the DrivAer reference model have been extensively investigated since its introduction in 2012. However, there is a relative lack of information relating to the models wake development resulting from the different rear-body configurations, particularly in the far-field. Given current interest in the aerodynamic interaction between two or more vehicles, the results from a preliminary CFD study are presented to address the development of the wake from the Fastback, Notchback, and Estateback DrivAer configurations. The primary focus is on the differences in the far-field wake and simulations are assessed in the range up to three vehicle lengths downstream, at Reynolds and Mach numbers of 5.2×106 and 0.13, respectively. Wake development is modelled using the results from a Reynolds-Averaged Navier-Stokes (RANS) simulation within a computational mesh having nominally 1.0×107 cells.

Cooling drag, typically known as the difference in drag coefficient between open and closed cooling configurations, has traditionally proven to be a difficult flow phenomenon to predict using computational fluid dynamics. It was seen as an academic yardstick before the advent of grille shutter systems. However, their introduction has increased the need to accurately predict the drag of a vehicle in a variety of different cooling configurations during vehicle development. This currently represents one of the greatest predictive challenges to the automotive industry due to being the net effect of many flow field changes around the vehicle. A comprehensive study is presented in the paper to discuss the notion of defining cooling drag as a number and to explore its effect on three automotive models with different cooling drag deltas using the commercial CFD solvers; STARCCM+ and Exa PowerFLOW.

The interactions between automatic controls, physics, and driver is an important step towards highly automated driving. This study investigates the dynamical interactions between human-selected driving modes, vehicle controller and physical plant parameters, to determine how to optimally adapt powertrain control to different human-like driving requirements. A cyber-physical system (CPS) based framework is proposed for co-design optimization of the physical plant parameters and controller variables for an electric powertrain, in view of vehicle’s dynamic performance, ride comfort, and energy efficiency under different driving modes. System structure, performance requirements and constraints, optimization goals and methodology are investigated. Intelligent powertrain control algorithms are synthesized for three driving modes, namely sport, eco, and normal modes, with appropriate protocol selections. The performance exploration methodology is presented.

The quantitative assessment and comparison of different hybrid vehicle options has traditionally been done on the basis of measuring or estimating the vehicle's fuel economy over predefined drive-cycles. In general, little or no consideration has been given to the more subjective and difficult to quantify vehicle requirements, such as trying to understand which derivative will be the most “fun” vehicle to drive. A lack of understanding in this area of vehicle performance sufficiently early within the development life-cycle so as to be in a position to influence the vehicle design, can lead to a compromised powertrain architecture which will ultimately increase the risk of product failure. The work presented within this paper constitutes part of the overall design activities associated with the LIFECar programme. The aim of the LIFECar consortium is to manufacture a lightweight, fuel cell hybrid electric sports vehicle.

In this paper, gear ratios of a two-speed transmission system are optimized for an electric passenger car. Quasi static system models, including the vehicle model, the motor, the battery, the transmission system, and drive cycles are established in MATLAB/Simulink at first. Specifically, since the regenerative braking capability of the motor is affected by the SoC of battery and motors torque limitation in real time, the dynamical variation of the regenerative brake efficiency is considered in this study. To obtain the optimal gear ratios, iterations are carried out through Nelder-Mead algorithm under constraints in MATLAB/Simulink. During the optimization process, the motor efficiency is observed along with the drive cycle, and the gear shift strategy is determined based on the vehicle velocity and acceleration demand. Simulation results show that the electric motor works in a relative high efficiency range during the whole drive cycle.

The vehicle dynamics control systems are traditionally based upon utilizing wheel brakes as actuators. However, there has been recently strong interest in the automotive industry for introduction of other vehicle dynamics actuators, in order to improve the overall vehicle stability, responsiveness, and agility features. This paper considers various actuators such as active rear and central differentials and active front and rear steering, and proposes design of related yaw rate control systems. Different control subsystems such as reference model, feedback and feedforward control, allocation algorithm, and time-varying controller limit are discussed. The designed control systems are verified and compared by computer simulation for double lane change and slalom maneuvers.

Autonomous vehicles have been shown to increase safety for drivers, passengers, and pedestrians and can also be used to maximize traffic flow, thereby reducing emissions and congestion. At the same time, governments around the world are promoting the usage of battery electric vehicles (BEVs) to reduce and control the emissions of CO2. This has made the development of autonomous vehicles and electric vehicles a very active research area and has prompted a significant amount of government funding. This article presents the detailed design of a low-cost platform for the development of an autonomous electric vehicle. In particular, it focuses on the design of the electrical architecture and the control strategy, tailored around the usage of affordable sensors and actuators. The specifications of the components are extensively discussed in relation to the performance target.

Energy management system designs for road vehicle applications have for some time considered the use of road data geospatial attributes such as elevation, speed limits and GPS derived online information, like traffic and position, to forecast the amount of fuel that could be consumed by a given vehicle on a specific route. This approach is especially useful when dealing with electrified platforms as on-board energy storage devices (such as fuel cells or batteries) have a lower energy density ratio [kJ/g]. Unfortunately within the tactical mobility context such information might not be readily available, either by passive obstructions, like mountains, or active ones due to jamming, etc. This paper will elaborate on an energy management system meant to deal with the uncertainty created by navigating in terrain where only basic trip information is available, such as probable distance to be travelled.

Customer feedback is normally fed into product design and engineering via quality surveys and therefore mainly comprises negative comments: complaints about things gone wrong. Whilst eradication of such problems will result in a feeling of satisfaction in existing customers, it will not instil the sense of delight required to attract conquest buyers. CUPID's aim is to conceive and evaluate ideas to stimulate product desirability through the provision of delightful features and execution. By definition, surprise and delight features cannot be foreseen, so we have to understand sensory appeal and, therefore, the “hidden” voice of the customer.

Simulations are presented which fully couple both the aerodynamics and cooling flow for a model of a fully engineered production saloon car (Jaguar XJ) with a two-tier cooling pack. This allows for the investigation of the overall aerodynamic impact of the under-hood cooling flow, which is difficult to predict experimentally. The simulations use a 100 million-element mesh, surface wrapped and solved to convergence using a commercially available RANS solver (STARCCM+). The methodology employs representative boundary conditions, such as rotating wheels and a moving ground plane. A review is provided of the effect of cooling flows on the vehicle aerodynamics, compared to published data, which suggest cooling flow accounts for 26 drag counts (0.026 Cd). Further, a sensitivity analysis of the pressure drop curves used in the porous media model of the heat exchangers is made, allowing for an initial understanding of the effect on the overall aerodynamics.

The aerodynamic drag of future low emission vehicles will need to be low. Unfortunately, vehicle shapes that result in low drag coefficients - of the order of 0.15 - are often aerodynamically unstable in crosswinds. The addition of wheels, transmission, radiators, suspension, steering, brakes, air ducts and wing mirrors can easily increase this drag coefficient to 0.24 and above and produce an undesirable lift distribution. The Aero-Stable Carbon Car (ASCC) is a research project, in conjunction with industrial partners, to design and build a practical 3 to 4 seat low drag car (CD less than 0.20) with an acceptable lift distribution (front to rear) which is also stable in crosswinds and in yaw through a series of low speed wind tunnel tests performed in the Cranfield College of Aeronautics 8′ × 6′ wind tunnel facility.

A mild hybrid powertrain with crankshaft mounted integrated motor generator (IMG) and torque controlled infinitely variable transmission (IVT) has shown clear potential for fuel economy (FE) enhancement. It also makes significant driveability and performance improvements possible which are a condition for customer satisfaction and subsequent marketability. The hybrid powertrain supervisory control strategy presented here uses the energy recovered during braking events for power assist, hence improving FE and driveability compromises. This is achieved by operating the engine at its best brake specific fuel consumption (BSFC) point during steady state conditions without deteriorating the transient response as a result of the comparatively fast IMG torque response. This paper demonstrates the launch manoeuvre and general driveability improvements achieved in simulation with validated models.

The application of hybridization technology is now widely regarded as a significant step forward to reduce fuel consumption and hence CO₂ emissions for ground vehicles. Many programs and much research has been done on these technologies in the automotive market, however little work has been done in the very cost sensitive market sector of the small motorcycle. This paper introduces and discusses the application of a low-cost hybrid technology to small motorcycles and scooters, and reviews some of the initial trade-offs through the use of a new hybrid simulation model developed at Cranfield University. The study being presented assessed the existing Energy Storage Systems (ESS) in the market. This list was reduced, omitting options which posed a clear safety or cost risk, or solutions which would disproportionally increased the Gross Vehicle Weight (GVW). Also omitted were storage options which could not be production ready in the near term, 3 - 5 years.

In jet atomization, breakup length is the length of the continuous jet segment, before its breakup to discontinuous droplets. Hydrodynamic instability theory, implemented in CFD codes, is often complemented by semi-empirical correlations for breakup length, which may limit parametric investigations. A basic mechanistic approach to the breakup length prediction, based on a simple momentum balance between the injected jet and the aerodynamic drag force due to the surrounding gas, which complements the classic hydrodynamic instability breakup mechanism, is suggested. This model offers a simple complementing mechanistic model. It is shown that obtained results compare well with published experiments, and with the established empirical correlation of Wu and Faeth (1995). A simplified version of the model, taking into account an inviscid hydrodynamic model is shown to maintain plausibility of breakup length predictions in fuel-injection relevant conditions.