Search Results

This paper presents an overview of the evolution & revolution of automotive E/E architectures and how we at Bosch, envision the technology in the future. It provides information on the bottlenecks for current E/E architectures and drivers for their evolution. Functionalities such as automated driving, connectivity and cyber-security have gained increasing importance over the past few years. The importance of these functionalities will continue to grow as these cutting-edge technologies mature and market acceptance increases. Implementation of these functionalities in mainstream vehicles will demand a paradigm shift in E/E architectures with respect to in-vehicle communication networks, power networks, connectivity, safety and security. This paper expounds on these points at a system level.

The spatial distribution of internal exhaust gas recirculation (EGR) is evaluated in an optically accessible direct injection spark ignition engine using near infrared laser absorption to visualize the distribution of the H2O molecule. The obtained overall internal exhaust gas recirculation compares well to gas-exchange cycle calculations and the spatial distributions are consistent with those measured with inverse LIF. The experimental procedures described in this report are designed to be simple and rapidly implemented without the need to resort to unusual optical components. The necessary spectral data of the selected absorption line is obtained from the HITEMP database and is validated with prior experiments carried out in a reference cell. Laser speckle in the images is effectively reduced using a ballistic diffuser.

The development of future automotive electronic systems requires new concepts in the software architecture, development methodology and information exchange. At Bosch an XML and MSR based technology is applied to achieve a consistent information handling throughout the entire software development process. This approach enables the tool independent exchange of information and documentation between the involved development partners. This paper presents the software architecture, the specification of software components in XML, the process steps, an example and an exchange scenario with an external development partner.

Car Periphery Supervision (CPS) systems comprise a family of automotive systems that are based on sensors installed around the vehicle to monitor its environment. The measurement and evaluation of sensor data enables the realization of several kinds of higher level applications such as parking assistance or blind spot detection. Although a lot of similarity can be identified among CPS applications, these systems are traditionally built separately. Usually, each single system is built with its own electronic control unit, and it is likely that the application software is bound to the controller's hardware. Current systems engineering therefore often leads to a large number of inflexible, dedicated systems in the automobile that together consume a large amount of power, weight, and installation space and produce high manufacturing and maintenance costs.

The emerging need of building an efficient Electric Vehicle (EV) charging infrastructure requires the investigation of all aspects of Vehicle-Grid Integration (VGI), including the impact of EV charging on the grid, optimal EV charging control at scale, and communication interoperability. This paper presents a cloud-based simulation and testing platform for the development and Hardware-in-the-Loop (HIL) testing of VGI technologies. Although the HIL testing of a single charging station has been widely performed, the HIL testing of spatially distributed EV charging stations and communication interoperability is limited. To fill this gap, the presented platform is developed that consists of multiple subsystems: a real-time power system simulator (OPAL-RT), ISO 15118 EV Charge Scheduler System (EVCSS), and a Smart Energy Plaza (SEP) with various types of charging stations, solar panels, and energy storage systems.

In order to reduce fuel consumption, companies have been looking at hybridizing vehicles. So far, two main hybridization options have been considered: electric and hydraulic hybrids. Because of light duty vehicle operating conditions and the high energy density of batteries, electric hybrids are being widely used for cars. However, companies are still evaluating both hybridization options for medium and heavy duty vehicles. Trucks generally demand very large regenerative power and frequent stop-and-go. In that situation, hydraulic systems could offer an advantage over electric drive systems because the hydraulic motor and accumulator can handle high power with small volume capacity. This study compares the fuel displacement of class 6 trucks using a hydraulic system compared to conventional and hybrid electric vehicles. The paper will describe the component technology and sizes of each powertrain as well as their overall vehicle level control strategies.

Modeling plume interaction and collapse for direct-injection gasoline sprays is important because of its impact on fuel-air mixing and engine performance. Nevertheless, the aerodynamic interaction between plumes and the complicated two-phase coupling of the evaporating spray has shown to be notoriously difficult to predict. With the availability of high-speed (100 kHz) Particle Image Velocimetry (PIV) experimental data, we compare velocity field predictions between plumes to observe the full temporal evolution leading up to plume merging and complete spray collapse. The target “Spray G” operating conditions of the Engine Combustion Network (ECN) is the focus of the work, including parametric variations in ambient gas temperature. We apply both LES and RANS spray models in different CFD platforms, outlining features of the spray that are most critical to model in order to predict the correct aerodynamics and fuel-air mixing.

For the development of future safety-relevant automotive electronic systems a thorough adaptation of the existing design process is necessary to consider safety and reliability in a more systematic way. In this paper an approach for a new design methodology is presented. It is based on the V-Model which is the established process model for the development of electronic and software systems in the automotive domain. For an advanced consideration of safety and reliability the existing process is extended by a second V (with process elements that have a special focus on safety and reliability) to a “Double V”. The new elements are interconnected with the existing ones at several points of time during the development process. By a defined information exchange between the two Vs continuity in the methodology is guaranteed. Basis for the extension are experiences of the aerospace domain that were adopted to automotive conditions.

A methodology has been developed for identifying the combination of battery characteristics which lead to least-cost electric vehicles. Battery interrelationships include specific power vs, specific energy, peak power vs. specific energy and DOD, cycle life vs. DOD, cost vs. specific energy and peak power, and volumetric and battery size effects. The method is illustrated for the “second car” mission assuming lead/acid batteries. Reductions in life-cycle costs associated with future battery research breakthroughs are estimated using a sensitivity technique. A research prioritization system is described.

A Machine Learning-Genetic Algorithm (ML-GA) approach was developed to virtually discover optimum designs using training data generated from multi-dimensional simulations. Machine learning (ML) presents a pathway to transform complex physical processes that occur in a combustion engine into compact informational processes. In the present work, a total of over 2000 sector-mesh computational fluid dynamics (CFD) simulations of a heavy-duty engine were performed. These were run concurrently on a supercomputer to reduce overall turnaround time. The engine being optimized was run on a low-octane (RON70) gasoline fuel under partially premixed compression ignition (PPCI) mode. A total of nine input parameters were varied, and the CFD simulation cases were generated by randomly sampling points from this nine-dimensional input space. These input parameters included fuel injection strategy, injector design, and various in-cylinder flow and thermodynamic conditions at intake valve closure (IVC).

This paper presents a unified modeling environment to simulate vehicle driving and powertrain operations within the context of the surrounding environment, including interactions between vehicles and between vehicles and the road. The goal of this framework is to facilitate the analysis of the energy impacts of vehicle connectivity and automation, as well as the development of eco-driving algorithms. Connectivity and automation indeed provide the potential to use information about the environment and future driving to minimize energy consumption. To achieve this goal, the designers of eco-driving control strategies need to simulate a wide range of driving situations, including the interactions with other vehicles and the infrastructure in a closed-loop fashion.

The Modular Automotive Technology Testbed (MATT) is a flexible platform built to test different technology components in a vehicle environment. This testbed is composed of physical component modules, such as the engine and the transmission, and emulated components, such as the energy storage system and the traction motor. The instrumentation on the tool enables the energy balance for individual components on drive cycles. Using MATT, a single set of hardware can operate as a conventional vehicle, a hybrid vehicle and a plug-in hybrid vehicle, enabling direct comparison of petroleum displacement for the different modes. The engine provides measured fuel economy and emissions. The losses of components which vary with temperature are also measured.

This paper describes the new Engine Management System (EMS) ME7. Torque and A/F demands for modern EMS result from both, internal functions (i.e. engine start, idle speed control, catalyst heating) and external systems (i.e. driver's request, transmission or vehicle dynamic control). With ME7 these demands are processed to the optimized actions of the actuators by a centrally coordinated torque and A/F management. The design of the functions is physically based to provide optimum portability and minimum calibration time. Examples are given for the physical manifold pressure model and the cylinder charge control of ME7 with electronic throttle control. The real time operating system „ERCOS” and a layer based software architecture enable the implementation of these functions in a flexible family of products for current and future systems.

A new combustion pressure sensor (CPS) for advanced engine management is presented, which is designed to carry out the functions: misfire detection, knock control, ignition control, camshaft phase detection and engine roughness control. For small size and high accuracy at a reasonable cost the piezoresistive effect, which is realized within an integrated circuit device and delivers low impedance output signals, has been chosen. Due to the optimized sensor housing, membrane and force transfer design, the sensor shows little offset drift when affected by flame front and environmental thermal stress. This paper describes the CPS and its performance in comparison with a well-known highly accurate reference sensor.

The functionality of engine management systems has grown rapidly over the last few years. The paper presents a new Motronic concept, the engine management control M3. The Motronic family M3 is a modular design destined to control engines with up to eight cylinders individually. The main features of this system and the ECU's concept are discussed.

This paper describes the concept of the Diagnostic System Management DSM which introduces an improved object-oriented software architecture in order to meet the high performance and reliability requirements of automotive On-Board Diagnostic Systems (OBD). DSM handles standard tasks and offers services to integrate diagnostic and control functions. This architecture enables the flexible composition of system-independent, reusable function implementations. Hence a distributed software development and software sharing are supported. The module DSM consists of a Fault Code Memory, an Inhibit Handler, a Validator and a Function Scheduler. Special care has been taken to achieve robustness against EMI effects. Bosch will use DSM in the future powertrain control systems.

Tapping of one or more torques (ranges 10 Nm and 60 Nm) on the steering column for the purpose of servo control must satisfy high accuracy requirements on the one hand and high safety requirements on the other hand. A suggestion for developing a low-cost solution to this problem is described below: Strain gages optimally satisfy both these requirements: However, for cost reasons, these are not applied directly to the steering column but to a prefabricated, flat steel rod which is laser welded to the torque rod of the steering column. The measuring direction of the strain gages is under 45° to the steering column axis. The strain gages are either vacuum metallized onto the support rod as a thin film or laminated in a particularly low-cost way by means of a foil-type intermediate carrier.

There are many challenges in implementing grid aware plug-in electric vehicle (PEV) charging systems with local load control. New opportunities for innovative load control were created as a result of changes to the 2014 National Electric Code (NEC) about automatic load control definitions for EV charging infrastructure. Stakeholders in optimized dispatch of EV charging assets include the end users (EV drivers), site owner/operators, facility managers and utilities. NEC definition changes allow for ‘over subscription’ of more potential EV charging station load than can be continuously supported if the total load at any time is within the supply system safety limit. Local load control can be implemented via compact submeter(s) with locally hosted control algorithms using direct communication to the managed electric vehicle supply equipment (EVSE).

Plug-in hybrid electric vehicle (PHEV) technologies have the potential for considerable petroleum consumption reductions, possibly at the expense of increased tailpipe emissions due to multiple “cold” start events and improper use of the engine for PHEV specific operation. PHEVs operate predominantly as electric vehicles (EVs) with intermittent assist from the engine during high power demands. As a consequence, the engine can be subjected to multiple cold start events. These cold start events may have a significant impact on the tailpipe emissions due to degraded catalyst performance and starting the engine under less than ideal conditions. On current hybrid electric vehicles (HEVs), the first cold start of the engine dictates whether or not the vehicle will pass federal emissions tests. PHEV operation compounds this problem due to infrequent, multiple engine cold starts.

Road vehicles can expend a significant amount of energy in undesirable vertical motions that are induced by road bumps, and much of that is dissipated in conventional shock absorbers as they dampen the vertical motions. Presented in this paper are some of the results of a study aimed at determining the effectiveness of efficiently transforming that energy into electrical power by using optimally designed regenerative electromagnetic shock absorbers. In turn, the electrical power can be used to recharge batteries or other efficient energy storage devices (e.g., flywheels) rather than be dissipated. The results of the study are encouraging - they suggest that a significant amount of the vertical motion energy can be recovered and stored.