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The present work represents the continuation of the introductory study presented in part I [11] where the experimental plan, the measurement system and the tools developed for the testing of a modern Wankel engine were illustrated. In this paper the motored data coming from the subsequent stage of the testing are presented. The AIE 225CS Wankel rotary engine produced by Advanced Innovative Engineering UK, installed in the test cell of the University of Bath and equipped with pressure transducers selected for the particular application, has been preliminarily tested under motored conditions in order to validate the data acquisition software on the real application and the correct determination of the Top Dead Centre (TDC) location which is of foremost importance in the computation of parameters such as the indicated work and the combustion heat release when the engine is tested later under fired conditions.

Particulate emissions from gasoline direct injection (GDI) engines continue to be a topic of substantial research interest. Forthcoming regulation both in the USA and the EU will further reduce their emission and drive innovation. Substantial research effort is spent undertaking experiments to understand, characterize, and research particle number (PN) emissions from engines and vehicles. Recent advances in computing power, data storage, and understanding of artificial intelligence algorithms now mean that these are becoming an important tool in engine research. In this work a random forest (RF) algorithm is used for the prediction of PN emissions from a highly boosted (up to 32 bar BMEP) GDI engine. Particle size, concentration, and the accumulation mode geometric standard deviation (GSD) are all predicted by the model. The results are analysed and an in depth study on parameter importance is carried out.

Wankel rotary engines are becoming an increasingly popular area of research with regard to their use as a range extender in the next generation of Hybrid Electric Vehicle (HEV). Due to their simple design, lightness, compactness and very favourable power-to-weight ratio, they represent one of the best alternative solutions to classic reciprocating piston engines. On the other hand, current Wankel engines still need improvements in terms of specific fuel consumption and emissions. This paper describes an innovative approach for the assessment of the performance of a modern rotary engine. All the experimental activities will be carried out within the Innovate UK funded ADAPT Intelligent Powertrain project led by Westfield Sportscars Limited.

The major contribution of this paper is the general description of a complete integrating procedure of autonomous vehicle system. Using Robot Operating System (ROS) as the framework, process from senor integration to path planning and path tracking were performed. Based on an off-road All-Terrain Vehicle, an Extended Kalman filter based autonomous control strategy was developed on the ROS. Both the position estimation and autonomous control were performed on the ROS platform. For the position estimation phase, sensory measurements from GPS, IMU and wheel odometry were acquired and processed on ROS. In accordance with the ROS architecture, separate packages were developed for each sensor to gather and publish corresponding measurements. Furthermore, Extended Kalman filtering was performed to fuse all sensory measurements to achieve an optimizing accuracy.

Delphi is developing a new combustion technology called Gasoline Direct-injection Compression Ignition (GDCI), which has shown promise for substantially improving fuel economy. This new technology is able to reuse some of the controls common to traditional spark ignition (SI) engines; however, it also requires several new sensors and actuators, some of which are not common to traditional SI engines. Since this is new technology development, the required hardware set has continued to evolve over the course of the project. In order to support this development work, a highly capable and flexible electronic control system is necessary. Integrating all of the necessary functions into a single controller, or two, would require significant up-front controller hardware development, and would limit the adaptability of the electronic controls to the evolving requirements for GDCI.

Current turbocharger models are based on characteristic maps derived from experimental measurements taken under steady conditions on dedicated gas stand facility. Under these conditions heat transfer is ignored and consequently the predictive performances of the models are compromised, particularly under the part load and dynamic operating conditions that are representative of real powertrain operations. This paper proposes to apply a dynamic mathematical model that uses a polynomial structure, the Volterra Series, for the modelling of the turbocharger system. The model is calculated directly from measured performance data using an extended least squares regression. In this way, both compressor and turbine are modelled together based on data from dynamic experiments rather than steady flow data from a gas stand. The modelling approach has been applied to dynamic data taken from a physics based model, acting as a virtual test cell.

Many More-Electric Aircraft (MEA) Electric Power System (EPS) architecture paradigms are being studied in order to provide the on-board electrical loads with high-quality supply and to ensure safe operation. EPS with dc distribution appears to be more promising due to higher efficiency, higher reliability, easier integration and lower overall weight. Another advantage of dc systems is the ease of sources paralleling, together with the optimization of load power sharing, this can lead to further EPS weight reduction. The DC bus can be fed by multiple sources such as generators, batteries and other energy storage devices. Many loads in MEA EPS are tightly controlled by power electronic converters and often behave as constant power loads (CPL). These are known as main contributors to the degradation of EPS stability margins. Therefore, stability study is one of the key topics in the assessment of potential EPS architecture candidates.

This paper describes the development and implementation of an Engine Drag Control algorithm to improve vehicle stability performance. Engine drag can occur on low and high coefficient surfaces when the driver suddenly releases the throttle. If the engine drag force becomes larger than the frictional force between the tire and the road, the tires will break loose from the surface and slip. This could induce vehicle instability especially with rear drive vehicles on low-coefficient surfaces. The EDC algorithm has been developed to provide accurate control of the wheels. EDC will help reduce the yaw rate of the vehicle and thus achieve greater vehicle stability. The paper also presents methods used to test the robustness of such a system. The purpose of the testing was to ensure that there would be no false activations of EDC under normal driving conditions and also to ensure that, when the system is active, it is mostly transparent to the driver.

Today automotive system suppliers develop more-or-less independent systems, such as brake, power steering and suspension systems. In the future, car manufacturers like Volvo will build up vehicle control systems combining their own algorithms with algorithms provided by automotive system suppliers. Standardization of interfaces to actuators, sensors and functions is an important enabler for this vision and will have major consequences for functionality, prices and lead times, and thus affects both vehicle manufacturers and automotive suppliers. The investigation of the level of appropriate interfaces, as part of the European BRAKE project, is described here. Potential problems and consequences are discussed from both a technical and a business perspective. This paper provides a background on BRAKE and on the functional decomposition upon which the interface definitions are based. Finally, the interface definitions for brake system functionality are given.

This paper presents a brake pressure estimation algorithm for Delphi Traction Control Systems (TCS). A control oriented lumped parameter model of a brake control system is developed using Matlab/Simulink. The model is derived based on a typical brake system and is generic to other types of brake control hardware systems. For application purposes, the model is simplified to capture the dominant dynamic brake pressure response. Vehicle experimental data collected under various scenarios are used to validate the algorithm. Simulation results show that the algorithm gives accurate pressure estimation. In addition, the calibration procedure is greatly simplified

This paper presents a theoretical and experimental study of a cylinder deactivation valvetrain system for the integration into an Engine Management System (EMS). A control-oriented lumped parameter model of the deactivation valvetrain system is developed and implemented using Matlab/Simulink, and validated by experimental data. Through simulation and experimental data analysis, the effect of operating conditions on the dynamic response is captured and characterized, over a wide range of operating conditions. The algorithm provides a basis for the calibration of the deactivation hardware. The generic characterization of the dynamic response can simplify the calibration parameters for the implementation in engine management systems.

This paper describes an environment for the development of production Engine Management Systems (EMS). This includes a formal framework and modeling methodology. The environment is based on using Simulink/Stateflow for developing a control system executable specification and a plant model. This allows for simulations of the system to be performed at the engineer's desk, which is identical performance with production software. We provide the details for incorporating production legacy code into the Simulink/Stateflow control system. The system includes a multi-rate, and event driven operating system. This system is developed to facilitate new algorithm development and automated software testing. Based on Simulink/Stateflow this specification will be suitable for use with commercial automatic code generation tools.

This paper describes the verification and comparison of position control algorithms for a continuously-variable cam phaser. Robust Engineering techniques are used. Two non-linear PID control algorithms are designed to control cam phaser position. The first algorithm is a more complex control strategy while the second is a thrifted approach that seeks to reduce throughput requirements. An L18 orthogonal array is established with noise factors that affect the quality of cam phaser control. Using the orthogonal array, the number of experiment test points required to characterize the control algorithm response is reduced from 8,748 to thirty-six. The test points of the orthogonal array are investigated experimentally on a motored engine outfitted with cam phaser hardware. The desired and actual cam position data are compared and analyzed for all points in the orthogonal array.

Automotive occupant safety continues to evolve. At present this area has gathered a strong consumer interest which the vehicle manufacturers are tapping into with the introduction of many new safety technologies. Initially, individual passive devices and features such as seatbelts, knee- bolsters, structural crush zones, airbags etc., were developed for to help save lives and minimize injuries in accidents. Over the years, preventive measures such as improving visibility, headlights, windshield wipers, tire traction etc., were deployed to help reduce the probability of getting into an accident. With tremendous new research and improvements in electronics, we are at the stage of helping to actively avoid accidents in certain situations as well as providing increased protection to vehicle occupants and pedestrians.

An algorithm for estimation of vehicle yaw rate and side slip angle using steering wheel angle, wheel speed, and lateral acceleration sensors is proposed. It is intended for application in vehicle stability enhancement systems, which use controlled brakes or steering. The algorithm first generates two initial estimates of yaw rate from wheel speeds and from lateral acceleration. A new estimate is subsequently calculated as a weighted average of the two initial ones, with the weights proportional to confidence levels in each estimate. This preliminary estimate is fed into a closed loop nonlinear observer, which generates the final estimate of yaw rate along with estimates of lateral velocity and side slip angle. Parameters of the observer depend on the estimated surface coefficient of adhesion, thus providing adaptation to changes in road surface coefficient of adhesion.

A finite element model of a folded airbag with the module cover and steering wheel system was developed to estimate the injury numbers of a 5th percentile female dummy in an out-of-position (OOP) situation. The airbag model was correlated with static airbag deployments and standard force plate tests. The 5th percentile finite element dummy model developed by First Technology Safety Systems (FTSS) was used in the simulation. The following two OOP tests were simulated with the airbag model including a validated steering wheel finite element model: 1. Chest on air bag module for maximum chest interaction from pressure loading (MS6-D) and 2. Neck on air bag module for maximum neck interaction from membrane loading (MS8-D). These two simulations were then compared to the test results. Satisfactory correlation was found in both the cases.

Both evaporative emissions and tailpipe emissions have been reduced by more than 90% from uncontrolled levels in state-of-the-art. However, now that the objective is to reach near-zero emission levels, the need for aggressive purging of the canister and fuel tank and the need for extremely precise control of engine Air/Fuel ratio (A/F) come into conflict. On-board diagnostics and the wide variation in operating conditions and fuel properties in the “real world” add to the challenge of resolving these conflicting requirements. An advanced canister purge algorithm has been developed which substantially eliminates the effect of canister purge on A/F control by estimating and compensating for the fuel and air introduced by the purge system. This paper describes the objectives and function of this algorithm and the validation of its performance.

Adaptive Cruise Control (ACC) technology is presently on the horizon as a convenience function intended to reduce driver workload. This paper presents an implementation of a brake algorithm, which extends the production cruise control feature. A brief overview of the system architecture and subsystem interfaces to the forward-obstacle detection system, throttle and engine management controls are described. Considerations of moding ACC with ABS and Traction Control are presented at the vehicle level. This development activity is presented in two major phases. Both phases of this development project utilize CAN controllers and transceivers to implement requirements for limited access highway driving. The initial phase of development requires the brake control to follow a deceleration command and operate “open-loop” to the vehicle controller. Vehicle test data capturing smooth stops on high coefficient surfaces is presented as insight to the braking performance of the vehicle.

It has been reported that lower extremity injuries represent a measurable portion of all moderate-to-severe automobile crash- related injuries. Thus, a simple tool to assist with the design of leg and foot injury countermeasures is desirable. The objective of this study is to develop a mathematical model which can predict load propagation and kinematics of the foot and leg in frontal automotive impacts. A multi-body model developed at the University of Virginia and validated for blunt impact to the whole foot has been used as basis for the current work. This model includes representations of the tibia, fibula, talus, hindfoot, midfoot and forefoot bones. Additionally, the model provides a means for tensioning the Achilles tendon. In the current study, the simulations conducted correspond to tests performed by the Transport Research Laboratory and the University of Nottingham on knee-amputated cadaver specimens.

A Barometric Pressure Estimator (BPE) algorithm was implemented in a production speed-density Engine Management System (EMS). The BPE is a model-based, easily calibrated algorithm for estimating barometric pressure using a standard set of production sensors, thereby avoiding the need for a barometric pressure sensor. An accurate barometric pressure value is necessary for a variety of engine control functions. By starting with the physics describing the flow through the induction system, an algorithm was developed which is simple to understand and implement. When used in conjunction with the Pneumatic and Thermal State Estimator (PSE and TSE) algorithms [2], the BPE requires only a single additional calibration table, generated with an automated processing routine, directly from measured engine data collected at an arbitrary elevation, in-vehicle or on a dynamometer. The algorithm has been implemented on several different engines.