A Hardware-in-the-Loop Facility for Integrated Vehicle Dynamics Control System Design and Validation

Due to the increased number and the complexity of the embedded systems in today’s vehicle, there is ever increasing pressure to reduce the development cost and time to market of such systems. In recent years, Model based Development (MBD) is becoming a main stream in the development of automotive embedded systems, and Hardware-in-the-Loop (HiL) testing is one of the key steps toward the implementation of MBD approach. This paper presents the recent HiL facility that has been developed at Cranfield University. The HiL setup includes real steering and brake smart actuator, high fidelity validated vehicle model, complete rapid control prototyping tool chain, and driver-in-the-loop capability. The applications of HiL setup are including but not limited to: smart actuators system identification; rapid control development and early validation of standalone and/or integrated vehicle dynamics control systems. Furthermore, the facility can be employed for investigation on driver-vehicle interaction at the presence of standalone active steering and/or brake systems as well as various Advanced Driver Assist Systems (ADAS), such as lane keeping or adaptive cruise control systems. The capability of the HiL facility for validation of a several newly developed vehicle dynamics control systems is presente

Virtual prototyping of vehicular electric steering assistance system using co-simulations

Virtual prototyping is a practical necessity in vehicle system development. From desktop simulation to track testing, several simulation approaches, such as co-simulation and hardware-in-loop (HIL) simulation, are used. However, due to interfacing problems, the consistency of testing results may not be ensured. Correspondingly, inherent inaccuracies result from numerical coupling error and non-transparent HIL interface, which involves control tracking error, delay error, and attached hardware and noise effects. This work aims to resolve these problems and provide seamless virtual prototypes for vehicle and electric power-assisted steering (EPAS) system development.The accuracy and stability of explicit parallel co-simulation and HIL simulation are investigated. The imperfect factors propagate in the simulation tools like perturbations, yield inaccuracy, and even instability according to system dynamics. Hence, reducing perturbations (coupling problem) and improving system robustness (architecture problem) are considered.In the coupling problem, a delay compensation method relying on adaptive filters is developed for real-time simulation. A novel co-simulation coupling method on H-infinity synthesis is developed to improve accuracy for a wide frequency range and achieve low computational cost. In the architecture problem, a force(torque)-velocity coupling approach is employed. The application of a force (torque) variable to a component with considerable impedance, e.g., the steering rack (EPAS motor), yields a small loop gain as well as robust co-simulation and HIL simulation. On a given EPAS HIL system, an interface algorithm is developed for virtually shifting the impedance, thus enhancing system robustness.The theoretical findings and formulated methods are tested on generic benchmarks and implemented on a vehicle-EPAS engineering case. In addition to the acceleration of simulation speed, accuracy and robustness are also improved. Consequently, consistent testing results and extended validated ranges of virtual prototypes are obtained

Radar Target Simulation for Vehicle-in-the-Loop Testing

Automotive radar sensors play a vital role in the current development of autonomous driving. Their ability to detect objects even under adverse conditions makes them indispensable for environment-sensing tasks in autonomous vehicles. As their functional operation must be validated in-place, a fully integrated test system is required. Radar Target Simulators (RTS) are capable of executing end-of-line, over-the-air validation tests by looping back a received and afterward modified radar signal and have been incorporated into existing Vehicle-in-the-Loop (ViL) test beds before. However, the currently available ViL test beds and the RTS systems that they consist of lack the ability to generate authentic radar echoes with respect to their complexity. The paper at hand reviews the current development stage of the research as well as commercial ViL and RTS systems. Furthermore, the concept and implementation of a new test setup for the rapid prototyping and validation of ADAS functions is presented. This represents the first-ever integrated radar validation test system to comprise multiple angle-resolved radar target channels, each capable of generating multiple radar echoes. A measurement campaign that supports this claim has been conducted

High performance control of a multiple-DOF motion platform for driver seat vibration test in laboratory

Dynamic testing plays an important part in the vehicle seat suspension study. However, a large amount of research work on vibration control of vehicle seat suspension to date has been limited to simulations because the use of a full-size vehicle to test the device is an expensive and dangerous task. In order to decrease the product development time and cost as well as to improve the design quality, in this research, a vibration generation platform is developed for simulating the road induced vehicle vibration in laboratory. Different from existing driving simulation platforms, this research focuses on the vehicle chassis vibration simulation and the control of motion platform to make sure the platform can more accurately generate the actual vehicle vibration movement. A seven degree-of-freedom (DOF) full-vehicle model with varying road inputs is used to simulate the real vehicle vibration. Moreover, because the output vibration data of the vehicle model is all about the absolute heave, pitch and roll velocities of the sprung mass, in order to simulate the vibration in all dimensions, a Stewart multiple-DOF motion platform is designed to generate the required vibration. As a result, the whole vibration simulator becomes a hardware-in-the-loop (HIL) system. The hardware consists of a computer used to calculate the required vibration signals, a Stewart platform used to generate the real movement, and a controller used to control the movement of the platform and implemented by a National Instruments (NI) CompactRIO board. The data, which is from the vehicle model, can be converted into the length of the six legs of the Stewart platform. Therefore, the platform can transfer into the same posture as the real vehicle chassis at that moment. The success of the developed platform is demonstrated by HIL experiments of actuators. As there are six actuators installed in the motion platform, the signals from six encoders are used as the feedback signals for the control of the length of the actuators, and advanced control strategies are developed to control the movement of the platform to make sure the platform can accurately generate the required motion even in heavy load situations. Theoretical study is conducted on how to generate the reasonable vibration signals suitable for vehicle seat vibration tests in different situations and how to develop advanced control strategies for accurate control of the motion platform. Both simulation and experimental studies are conducted to validate the proposed approaches

Holistic simulation for integrated vehicle design

A holistic vehicle simulation capability is necessary for front-loading component, subsystem, and controller design, for the early detection of component and subsystem design flaws, as well as for the model-based calibration of powertrain control modules. The current document explores the concept of holistic vehicle simulation by means of reviewing the current trends automotive system design and available solutions in terms of model interfaces and neutral modelling environments. The review is followed by the presentation of a Simulink-based Multi- disciplinary Modelling Environment (MME) developed by the authors to accommodate simulation work across the vehicle development cycle

HAPTICS IN ROBOTICS AND AUTOMOTIVE SYSTEMS

Haptics is the science of applying touch (tactile) sensation and control to interaction with computer applications. The devices used to interact with computer applications are known as haptic interfaces. These devices sense some form of human movement, be it finger, head, hand or body movement and receive feedback from computer applications in form of felt sensations to the limbs or other parts of the human body. Examples of haptic interfaces range from force feedback joysticks/controllers in video game consoles to tele-operative surgery. This thesis deals with haptic interfaces involving hand movements. The first experiment involves using the end effector of a robotic manipulator as an interactive device to aid patients with deficits in the upper extremities in passive resistance therapy using novel path planning. The second experiment involves the application of haptic technology to the human-vehicle interface in a steer-by-wire transportation system using adaptive control

The Impact of Virtual Environments for Future Electric Powered-Mobility Development Using Human-in-the-Loop: Part A - Fundamental Design and Modelling

The use of virtual tools will be discussed across two complimentary chapters, Part A explores the fundamental concepts of electric vehicle systems modelling and a design procedure for human-in-the-loop virtual environments; Part B demonstrates how this architecture can be applied to assess energy optimization strategies. In Part A, this research investigates the design and implementation of simulation tools used to predict the energy consumption and strategic tool for the development of an electric vehicle. The case study used is an electric prototype race car for Ene-1 GP SUZUKA competition. Engineering effort is re-directed from physical product design, optimisation and validation to digital tools, processes and virtual testing. This virtual platform is characterised by the integration of two different simulation models—mathematical model of the electric vehicle systems represented by Matlab/Simulink, which accounts for the representation of the powertrain performance prediction that taking into account the resistance motion; and a virtual environment represented by Cruden Software, which accounts recreate topography of real world environment in a driving simulator and incorporate human driver behaviour