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This paper describes a framework for modeling and validating distributed real-time embedded control systems. The modeling component of the framework combines executable architectural specifications with component models in notations such as Simulink and Stateflow to yield simulate-able models of distributed systems. The paper then discusses techniques for comparing the behavior of these system models with idealized control specifications given in Simulink / Stateflow. The framework is intended to support design processes in which a controls engineer develops a controller model that is then used as a specification by a system-engineering team responsible for a system model that may involve deployment-platform details.

AUTOSAR is a partnership of automotive manufacturers and suppliers. The main objective of AUTOSAR is to develop a standard for automotive E/E architectures that will enable further functional growth within the automotive industry. Further, the standard will support current and future safety related functions such as active chassis control and active safety. The responsibility of safety within AUTOSAR is to a large extent given to the Safety Team. This paper presents the approach taken by this team and its deliverables.

With the rapid development of modern economy and society, traffic congestion has become an increasingly serious problem. Vehicle cooperative driving can alleviate traffic congestion and improve road traffic capacity. Compare with vehicle separate control, cooperative driving combines various vehicle systems, and highly integrates information on obstacle location, vehicle status and driving intention. Then the controller uniformly issues instructions to ensure the orderly driving of the platoon. In the cooperative driving platoon, the displacement difference and the speed difference between vehicles have a certain relationship, which reduces the possibility of traffic accidents and then improves the safety of driving. In the process of cooperative driving, if there are multiple vehicles whose speeds don’t meet the current lane requirements, or if there are obstacles ahead, multi-vehicle lane change measures must be taken.

Range-extended hybrids are an attractive option for medium- and heavy-duty commercial vehicle fleets because they offer the efficiency of an electrified powertrain with the driving range of a conventional diesel powertrain. The vehicle essentially operates as if it was purely electric for most trips, while ensuring that all commercial routes can be completed in any weather conditions or geographic terrain. Fuel use and point-source emissions can be significantly reduced, and in some cases eliminated, as many shorter routes can be fully electrified with this architecture. Under a U.S. Department of Energy (DOE)-funded project for Medium- and Heavy-Duty Vehicle Powertrain Electrification, Cummins has developed a plug-in hybrid electric Class 6 truck with a range-extending engine designed for pickup and delivery application.

When the air conditioning (A/C) is turned on, the intake air to the HVAC is cooled at the evaporator. This is not only used for cooling the air temperature but also to dehumidify. Therefore, for a typical automatic climate control system, A/C will automatically operate even in winter (cold ambient temperature conditions) in order to prevent the windows from fogging despite its effect on fuel economy. In some applications, a humidity sensor is installed on top of the windshield and when the probability of fogging is low the A/C operation is disabled automatically to prevent unnecessary compressor operation which can increase fuel consumption. However, humidity sensor is not widely adopted as it requires some space to be installed and the cost is relatively expensive compared with other HVAC equipped sensors. In this study, a system was invented that disables the compressor operation when the fogging probability is low without using the conventional humidity sensor.

Vehicular control systems are characterized with numerous complex interactions with a steady rise of autonomous functions, which makes it more challenging for designers and safety engineers to identify unexpected failures. These systems tend to be highly integrated and exhibit features like concurrency for which traditional verification and validation techniques (i.e. testing and simulation) are insufficient to provide rigorous and complete assessment. Model Checking, a well-known formal verification technique, can be used to rigorously prove the correctness of such systems according to design Requirements. In particular, Model Checking is a method for formally verifying finite-state concurrent systems. Specifications about the system are expressed as temporal logic formulas, and efficient symbolic algorithms are used to traverse the model defined by the system and check if the specification holds or not.

Emissions of particulate matter, or PM, due to brake wear, are not well quantified in current air pollutant emission inventories. Current emission factor models need to be updated to reflect new technologies and materials and to incorporate the effects of changing driving habits and speeds. While emission regulations drive technical innovations that are significantly reducing PM emissions in vehicle exhaust, non-exhaust automotive emissions remain unregulated. Current emission factor models need to be updated to reflect the changes caused by new technologies, materials, and speed-dependent vehicle usage. Most research regarding brake emissions relies on a laboratory setting. Laboratory testing has allowed researchers, application engineers, data modeling engineers, and environmental agencies to generate large datasets for multiple vehicle configurations and friction couple designs.

Heavy-duty vehicles represent a significant portion of road transport and they need to operate in a clean and efficient manner. Their emission control systems need to be enhanced to sustain the high conversion efficiencies seen during motorway conditions inother operating conditions. The European Commission is developing legislative proposals for Euro 7 emissions regulations for light- and heavy-duty vehicles. The new Euro 7regulation will likely focus on ensuring the emissions from heavy-duty vehicles are minimized over extensive on-road operating conditions and specifically on operating conditions such as urban driving and cold-start operation. These challenges are increased by the need to ensure low secondary emissions like NH3 and N2O, as well as a low impact on CO2 emissions. The paper outlines the low pollutant emissions achieved by a heavy-duty Diesel demonstrator vehicle.

This paper describes a system-level view of a fully automated transit system comprising a fleet of automated vehicles (AVs) in driverless operation, each with an SAE level 4 Automated Driving System, along with its related safety infrastructure and other system equipment. This AV system-level control is compared to the automatic train control system used in automated guideway transit technology, particularly that of communications-based train control (CBTC). Drawing from the safety principles, analysis methods, and risk assessments of CBTC systems, comparable functional subsystem definitions are proposed for AV fleets in driverless operation. With the prospect of multiple AV fleets operating within a single automated mobility district, the criticality of protecting roadway junctions requires an approach like that of automated fixed-guideway transit systems, in which a guideway switch zone “interlocking” at each junction location deconflicts railway traffic, affirming safe passage.

The primary function of exhaust muffler is to reduce noise from the internal combustion engine without affecting its performance due to the impact of higher back pressure. The exhaust system back pressure is directly related to the engine fuel efficiency. The consumption of back pressure by the emission control system in BS IV regulation is about 30% from the total permissible engine limit, whereas in BS VI consumption is about 70%. The combination technologies used in BSVI and forthcoming RDE regulations such as TWC, GPF, DOC, DPF and SCR increases significant back pressure in exhaust system, hence the engine performance decreases. This demand robust method to control the exhaust back pressure for better fuel efficiency. Emission, noise and back pressure are the non-complimentary parameters in exhaust system development. The variable valve technology introduction in muffler is one method to optimize the above parameters.

As a race driver hits the pedal to trigger the braking event, a dynamic load transfer takes place in the car. This is a similar kind of weight transfer experienced on the road while stopping any vehicle abruptly. Modern race cars such as FIA-regulated Grand Touring Car classes GT3 and LMGTE produce a significant aerodynamic downforce at a reasonably high efficiency level. In this type of high downforce race cars, load variations originated by aerodynamics are added onto the mass transfer. The combination of these effects provide a braking effect with this type of cars a highly transient character. At the same time, our customers are facing the challenge of strict technical regulations, usually forbidding brake control systems. In motorsport competition, car performance is of primary priority to help our customers win championships.

Linear engine alternator (LEA) design optimization traditionally has been difficult because each independent variable alters the motion with respect to time, and therefore alters the engine and alternator response to other governing variables. An analogy is drawn to a conventional engine with a very light flywheel, where the rotational speed effectively is not constant. However, when springs are used in conjunction with an LEA, the motion becomes more consistent and more sinusoidal with increasing spring stiffness. This avoids some attractive features, such as variable compression ratio HCCI operation, but aids in reducing cycle-to-cycle variation for conventional combustion modes. To understand the cycle-to-cycle variations, we have developed a comprehensive model of an LEA with a 1kW target power in MATLAB®/Simulink, and an LEA corresponding to that model has been operated in the laboratory.

This paper presents innovative methods to resolve the two challenges that occur when using a switched reluctance motor (SRM) as a traction motor for a compact electric vehicle (EV). Electric vehicles (EVs) are seeing a rise in popularity today and the demand for further advancement of EV technologies will continue to grow. Induction motors and interior permanent magnet motors (IPMs) are most commonly used traction motors for EVs. In this project, we focused on the development of a switched reluctance motor (SRM) as an alternative motor for compact EVs, leveraging the following benefits of SRMs: 1) SRMs, which require no permanent magnets, have no drag torque, enabling clutchless motor applications, and 2) SRMs demonstrate high efficiency in the high-speed rotation range. In applications of SRMs as EV drivers, however, there are two challenges to be resolved. The first challenge is that SRMs have significant torque ripples due to the principle of torque generation.

In this paper a method for the identification of most significant vehicle parameters influencing the behavior of a lateral control system of autonomous car is presented. Requirements for the design stage of the controller need to consider many uncertainties in the plant. While most vehicle properties can be compensated by an appropriate tuning of the control parameters, other vehicle properties can change significantly during usage. The control system is evaluated based on performance measures. Analyzed parameters comprise functional tire characteristics, mass of the vehicle and position of its center of gravity. Since the parameters are correlated, but Sobol’ sensitivity analysis assumes decorrelated inputs, random variation yields no reasonable results. Furthermore, the variation of each parameter or set of parameters is not applicable since the numbers of required simulations is increased significantly according to input dimension.

Automotive exhaust noise is one of the major sources of noise pollution and it is controlled by passive control system (mufflers) and active control system (loudspeakers and active control algorithm). Mufflers are heavy, bulky and large in size while loudspeakers have a working temperature limitation. Carbon nanotube (CNT) speakers generate sound due to the thermoacoustic effect. CNT speakers are also lightweight, flexible, have acoustic and light transparency as well as high operating temperature. These properties make them ideal to overcome the limitations of the current exhaust noise control systems. An enclosed, coaxial CNT speaker is designed for exhaust noise cancellation application. The development of a 3D multi-physics (coupling of electrical, thermal and acoustical domains) model, for the coaxial speaker is discussed in this paper. The model is used to simulate the sound pressure level, input power versus ambient temperature and efficiency.

Aircraft production is facing various technical challenges, such as large product dimensions, complex joining processes, and organization of assembly tasks. Overcoming such challenges, as well as maintaining low tolerances and small batch sizes, is often difficult to achieve whilst retaining economic viability. ZeMA believes that a semi-automated approach is the most effective way to optimize aircraft section assembly. This can be achieved with a semi-automated riveting process for solid rivets, using Human-Robot-Collaboration in combination with an intuitive Human-Machine-Interaction operating concept. In the assembly of aircraft structures - in this scenario the aircraft aft section - the pressure bulk head is mounted to the section barrel. Two operators work collaboratively in uncomfortable, non-ergonomic positions, yet of course have to maintain exacting quality standards.

Most stringent emission legislations have been implemented in all major markets to improve air quality across the past years. This effects the product cost of the vehicles which is considered being critical and needs to be minimized. India suffers from bad air quality and countermeasures have been defined. One being the implementation of similar emission standards than EU VI. By doing so, India takes a large step going from the currently effective BS IV directly to BS VI. Emission reduction is currently mainly handled by the usage of EGR, thus no engine aftertreatment system has been applied. BS VI will require an aftertreatment (EAS) concept with several catalysts and corresponding control system. India is a very cost sensitive market and a carry over of solutions from the EU needs to be evaluated carefully and new approaches need to be found.

Tire inflation pressure has a significant impact over vehicle driving dynamics, fuel consumption as well as tire life. Therefore, continuous monitoring of tire pressure becomes imperative for ride comfort, safety and optimum vehicle handling performance. Two types of tire pressure monitoring systems (TPMS) used by vehicles are - direct and indirect TPMS. Direct systems deploy pressure sensors at each wheel and directly send pressure value to the vehicle Controller Area Network (CAN). Indirect sensors on the other hand use the information from already existing sensors and some physics-based equations to predict the value of tire pressure. Direct TPMS tend to be more accurate but have higher cost of installation while indirect TPMS comes with a minimum cost but compromised accuracy. A digital proof-of-concept study for indirect TPMS development of a non-ESP vehicle based on machine learning (ML) technique is elaborated in this paper.

A key enabler to maximizing the benefits from advanced powertrain technologies is to adopt a systems integration approach and develop optimized controls that consider the propulsion system and vehicle as a whole. This approach becomes essential when incorporating Advanced Driver Assistance Systems (ADAS) and communication technologies, which can provide information on future driving conditions. This may enable the powertrain control system to further improve the vehicle performance and energy efficiency, shifting from an instantaneous optimization of energy consumption to a predictive and “look-ahead” optimization. Benefits from this approach can be realized at all levels of electrification, from conventional combustion engines to hybrid propulsion systems and full electric vehicles, and at all levels of vehicle automation.

The backlash between engaging components in a driveline is unavoidable, especially when the gear runs freely and collides with the backlash, the impact torque generated increases the vibration amplitude. The power-split hybrid electric vehicle generates output torque only from the traction motor during the launching process. The nonlinear backlash can greatly influence the driveability of the driveline due to the rapid response of the traction motor and the lack of the traditional clutches and torsional shock absorbers in the powertrain. This paper focuses on the launch vibration of the power-split hybrid electric vehicle, establishes a nonlinear driveline model considering gear backlash, including an engine, two motors, a Ravigneaux planetary gear set, a reducer, a differential, a backlash assembly, half shafts, and wheels.