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The rise of Software-Defined Vehicles (SDV) has rapidly advanced the development of Advanced Driver Assistance Systems (ADAS), Autonomous Vehicle (AV), and Battery Electric Vehicle (BEV) technology. While AVs need power to compute data from perception to controls, BEVs need the efficiency to optimize their electric driving range and stand out compared to traditional Internal Combustion Engine (ICE) vehicles. AVs possess certain shortcomings in the current world, but SAE Level 2+ (L2+) Automated Vehicles are the focus of all major Original Equipment Manufacturers (OEMs). The most common form of an SDV today is the amalgamation of AV and BEV technology on the same platform which is prominently available in most OEM’s lineups. As the compute and sensing architectures for L2+ automated vehicles lean towards a computationally expensive centralized design, it may hamper the most important purchasing factor of a BEV, the electric driving range.

Driver Assistance and Autonomous Driving features are becoming nearly ubiquitous in new vehicles. The intent of the Driver Assistant features is to assist the driver in making safer decisions. The intent of Autonomous Driving features is to execute vehicle maneuvers, without human intervention, in a safe manner. The overall goal of Driver Assistance and Autonomous Driving features is to reduce accidents, injuries, and deaths with a comforting driving experience. However, different drivers can react differently to advanced automated driving technology. It is therefore important to consider and improve the adaptability of these advances based on driver behavior. In this paper, a human-centric approach is adopted to provide an enriching driving experience. We perform data analysis of the naturalistic behavior of drivers when performing lane change maneuvers by extracting features from extensive Second Strategic Highway Research Program (SHRP2) data of over 5,400,000 data files.

Pre-chamber ignition is one of the advanced technologies to improve the combustion performance for lean combustion natural gas engine, which could achieve low NOx, simultaneously. The designing scheme of the orifices, which connects the pre-chamber and the main chamber, is the main challenge limiting the further improvement. In this work, the three-dimensional computational fluid dynamics calculation based on a four-stroke engine with 320 mm cylinder bore was conducted to investigate the effects of orifice structure on the combustion and NOx performance. The results show that the schemes with 7 and 9 orifices lead to the delayed high-temperature jets formation due to the asymmetrical airflow in the pre-chamber, which retards the ignition timing but enhances the combustion in the main chamber. The 6 orifices scheme leads to the insufficient distribution of the high-temperature jets, and the 10 orifices result in the serious interference between the adjacent high-temperature jets.

For liquid fueled engine, the fuel atomization affects fuel’s evaporation, combustion, noise and vibration characteristics eventually. In this study, the effects of fuel species on the internal flow and near field primary breakup characteristics of a nozzle “Spray C” are investigated. Based on the framework of OpenFOAM, the newly developed solver which coupled cavitation model and the multifluid-quasi-VOF (Volume-of-Fluid) model, and combines the LES (Large Eddy Simulation) are applied to simulate the nozzle inner flow and near field jet breakup when using diesel and biodiesel respectively. The transient characteristics of nozzle inner flow and near field spray of two different fuels were analyzed, and the variation of axial pressure and velocity of nozzle was obtained. The simulation results show that the cavitation of biodiesel with high viscosity and low saturated vapor pressure develops slower and weaker.

Structural Health Monitoring (SHM), especially in the field of rotary machinery diagnosis, plays a crucial role in determining the defect category as well as its intensity in a machine element. This paper proposes a new framework for real-time classification of structural defects in a roller bearing test rig using time domain-based classification algorithms. Along with the bearing defects, the effect of eccentric shaft loading has also been analyzed. The entire system comprises of three modules: sensor module – using accelerometers for data collection, data processing module – using time-domain based signal processing algorithms for feature extraction, and classification module – comprising of deep learning algorithms for classifying between different structural defects occurring within the inner and outer race of the bearing.

Multi-sensor fusion strategies have gradually become a consensus in autonomous driving research. Among them, radar-camera fusion has attracted wide attention for its improvement on the dimension and accuracy of perception at a lower cost, however, the processing and association of radar and camera data has become an obstacle to related research. Our approach is to build a concise framework for camera and radar detection and data association: for visual object detection, the state-of-the-art YOLOv5 algorithm is further improved and works as the image detector, and before the fusion process, the raw radar reflection data is projected onto image plane and hierarchically clustered, then the projected radar echoes and image detection results are matched based on the Hungarian algorithm. Thus, the category of objects and their corresponding distance and speed information can be obtained, providing reliable input for subsequent object tracking task.

The traditional MTPA-flux weakening control method depends on the off-line calibration and PI feedback(leading angle control method). This will cause insufficient responsiveness if the motor parameters change. This paper proposes a novel MTPA-flux weakening feedforward control strategy based on model parameter updates. To reduce the real-time calculation load, the Ferrari collocation method is used to solve the quartic equation to obtain the MTPA explicit format model, and the discrete bisection method is used to quickly solve the working point in the flux weakening stage. By judging the relationship among the target torque working line, the voltage limiting circle and the current limiting circle, the intersection point with the minimum current loss is selected as the working point. The advantages of the designed MTPA-flux weakening feedforward control strategy are verified by implementing the simulation based on a permanent magnet synchronous motor model.

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.

A drag coefficient, which is representative of the drag of a car undergoing a particular drive cycle, known as the cycle-averaged-drag coefficient, has been previously developed. It was derived for different drive cycles using mean values for the natural wind. It assumed terrain dependent wind velocities based on the Weibull function, equi-probable wind direction and shear effects. It did not, however, include any effects of turbulence in the natural wind. Some recent research using active vanes in the wind tunnel to generate turbulence has suggested that the effect on drag can be evaluated from the quasi steady wind inputs. On this basis a simple quasi-steady theory for the effect of turbulence on car drag is developed and applied to predicting the cycle-averaged-drag coefficient for a range of cars of different types. The drag is always increased by the turbulence but in all cases is relatively small.

GTDI engines are becoming more efficient, whether individually or part of a HEV (Hybrid Electric Vehicle) powertrain. For the latter, this efficiency manifests itself as increase in zero emissions vehicle mileage. An ideal device for energy recovery is a turbogenerator (TG), and, when placed downstream the conventional turbine, it has minimal impact on catalyst light-off and can be used as a bolt-on aftermarket device. A Ricardo WAVE model of a representative GTDI engine was adapted to include a TG (Turbogenerator) and TBV (Turbine Bypass Valve) with the TG in a mechanical turbocompounding configuration, calibrated using steady state mapping data. This was integrated into a co-simulation environment with a SISO (Single-Input, Single-Output) dynamic controller developed in SIMULINK for the actuator control (with BMEP, manifold air pressure and TG pressure ratio as the controlled variables).

The influence of driver modeling and drive cycle target speed trace modification on vehicle dynamics within energy consumption simulations is studied. EPA dynamometer speed error criteria and the SAE J2951 Drive Quality Evaluation for Chassis Dynamometer Testing standard are applied to simulation outputs as proposed components of simulation validation, providing guidelines for acceptable vehicle speed outputs and allowing comparison of simulation results to reported EPA dynamometer test statistics. The combined effect of driver model tuning and drive cycle interpolation methods is investigated for the UDDS, HwFET and US06 drive cycles, with EPA-specified linearly interpolated speed trace and a PI controller driver as a baseline result.

Wet Clutches are used in automotive powertrains to enable compact designs and efficient gear shifting. During the slip phase of engagement, significant flash temperatures arise at the friction disc to separator interface because of dissipative frictional losses. An important aspect of the design process is to ensure the interface temperature does not exceed the material temperature threshold at which accelerated wear behavior and/or thermal degradation occurs. During the early stages of a design process, it is advantageous to evaluate numerous system and component design iterations exposed to plethora of possible drive cycles. A simulation tool is needed which can determine the critical operational conditions the system must survive for performance and durability to be assured. This paper describes a time-efficient multiphysics model developed to predict clutch disc temperatures with a runtime in the order of minutes.

To improve the state of the art in automotive aerodynamic prediction using CFD, it is important to compare different CFD methods, software and modelling for standardized test cases. This paper reports on the 2nd Automotive CFD Prediction Workshop for the Windsor body squareback test case. The Windsor model has high quality experimental data available and a simple geometry that allows it to be simulated with limited computational resources. The model is 1 metre long and operates at a Reynolds number of 2.7 million. The original Windsor model did not include wheels, but a second variant was added here with non-rotating wheels. Experimental data is available for integrated forces, surface pressure and wake PIV surveys. Eight standard meshes were provided, covering the two geometry variants, two near wall mesh spacings (relating to wall resolved and wall modelled) and two mesh densities in the wake (relating to RANS and eddy resolving).

A new and unique electric vehicle powertrain model based on bidirectional power flow for propel and regenerative brake power capture is developed and applied to production battery electric vehicles. The model is based on a Willans line model to relate power input from the battery and power output to tractive effort, with one set of parameters (marginal efficiency and an offset loss) for the bidirectional power flow through the powertrain. An electric accessory load is included for the propel, brake and idle phases of vehicle operation. In addition, regenerative brake energy capture is limited with a regen fraction (where the balance goes to friction braking), a power limit, and a low-speed cutoff limit. The purpose of the model is to predict energy consumption and range using only tractive effort based on EPA published road load and test mass (test car list data) and vehicle powertrain parameters derived from EPA reported unadjusted UDDS and HWFET energy consumption.

The effects of adding a streamlined tail to a simple vehicle shape, represented by the Windsor Body has been investigated in a small scale wind tunnel experiment. The extended tail has a constant width, with a flat lower surface and a constant upper surface taper angle. The tail is truncated in steps to understand the trends in the principal aerodynamic characteristics. The slant surface and the base have been pressure tapped to indicate the contribution to drag and lift from these surfaces. The bodies have been tested over a range of yaw angles and wind tunnel airspeeds. The effects of adding wheels, albeit in a fixed ground experiment, has also been studied. The experimental data for the basic wheel-less body in a squareback configuration and with tapered tails of different length at zero yaw has been compared with an earlier CFD simulation of the same configurations.

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.

Vehicle development involves the design and integration of subsystems of different domains to meet performance, efficiency, and emissions targets set during the initial developmental stages. Before a physical prototype of a vehicle or vehicle powertrain is tested, engineers build and test virtual prototypes of the design(s) on multiple stages throughout the development cycle. In addition, controllers and physical prototypes of subsystems are tested under simulated signals before a physical prototype of the vehicle is available. Different departments within an automotive company tend to use different modelling and simulation tools specific to the needs of their specific engineering discipline. While this makes sense considering the development of the said system, subsystem, or component, modern holistic vehicle engineering requires the constituent parts to operate in synergy with one-another in order to ensure vehicle-level optimal performance.

Many modern vehicles have blunt rear end geometries for design aesthetics and practicality; however, such vehicles are potentially high drag. The application of tapering; typically applied to an entire edge of the base of the geometry is widely reported as a means of reducing drag, but in many cases, this is not practical on real vehicles. In this study side tapers are applied to only part of the side edge of a simplified automotive geometry, to show the effects of practical implementations of tapers. The paper reports on a parametric study undertaken in Loughborough University’s Large Wind Tunnel with the ¼ scale Windsor model equipped with wheels. The aerodynamic effect of implementing partial side edge tapers is assessed from a full height taper to a 25% taper in both an upper and lower body configuration. These were investigated using force and moment coefficients, pressure measurements and planar particle image velocimetry (PIV).

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.