Advanced Microsystems for Automotive Applications 2012

Current limitations of battery systems for fully electric vehicles (FEV) are mainly related to performance, driving range, battery life, re-charging time and price per unit. New cell chemistries are able to mitigate these drawbacks, but are more prone to catastrophic failures due to a thermal runaway than current solutions. Therefore, new and more advanced management strategies are necessary to be able to safely prevent the energy storage system from ever coming into this critical situation. In this paper, a novel battery management system (BMS) architecture is introduced, which will be able to meet these high requirements by introducing a network that has smart satellite systems in each macro-cell or even in each individual cell. In addition, the issues of safety and reliability to be considered for the integration and packaging technologies of the smart satellite systems will be described as well. The work reported is part of the European project ‘Smart-LIC’, which is supported by EPoSS, and the German project ‘HotPowCon’.

The market breakthrough of electric vehicles is mainly delayed by the still too high costs of the battery system. The smart battery cell monitoring presented in this article enables further cost reduction. It consists of battery cells integrating the monitoring electronics together with a data transfer interface for communicating in a bidirectional way with the battery management system. The data transfer interface presented in this paper is based on a differential contactless data transmission bus using galvanically isolated, capacitively coupled links to each single smart battery cell. Since neither galvanic contacts nor connectors are needed, the proposed concept provides simultaneously a very high level of reliability and robustness, and a highly cost-efficient manufacturing process, thus allowing a significant reduction of the final battery pack costs. This paper describes a possible implementation of such a differential contactless data transmission for monitoring and managing battery cells in electric vehicles.

Monitoring the state of charge of batteries in start-stop, hybrid- and electrical vehicles makes precise current sensing one of the key functions of today’s and future car architectures. Huge required measurement ranges of up to ±600A conflict with fine resolution and high precision requirements - which currently could only be solved by using high performance shunts in connection with specialized ICs offering highest resolution ADCs. The invention follows the approach of a variable, percentage resolution, offering required fine resolution at low currents and the minimum required resolution at high currents. A realization approach using state-of-the-art MOSFET technology and innovative control loop design with a standard

μ

C is presented.

This paper is aimed at comparing two designs, one comprising gaps in its magnetic circuit, the other one without, for a power inductor operating in the medium frequency range (10 - 20 kHz) and crossed by a triangular current superimposed with a DC bias. The goal is to find the design that satisfies the target inductance value using the minimum volume of materials. Two kinds of material are considered for the magnetic core: soft amorphous alloy to be used with the gapped configuration and powder to be used with the gapless one. The designs are calculated through a process that includes an analytical preliminary calculation and a numerical optimization. In the case of soft magnetic alloy, the magnetic non-linearity of the material is neglected in the analytical model. On the contrary, non-linearity of powder material can not be neglected. It requires the use of an iterative calculation. The numerical optimization is based on 2D Finite Element Analysis associated to a Simplex-type algorithm. It completes the analytical calculation to reach an appropriate solution for which the target inductance and minimum volume are reached simultaneously.

The last few years have seen electric vehicle technology develop in leaps and bounds. EVs are now universally recognised as the future of the automotive industry, with cars such as the Nissan Leaf entering the market in 2011. However, there is no doubt that barriers to mass-market adoption still remain, primarily in terms of efficiency, cost and usability. It is these issues that are now being addressed by the development of wireless charging technology. Simplicity and minimum driver intervention are key features that win out time-andtime again and when these features are coupled with high power transfer efficiency, wireless charging is a winning combination. This presentation will outline how this technology works and the benefits it is set to bring to the electric vehicle industry.

Contactless energy transfer between power supply and electric vehicle as described in this proposal is based on the principle of resonant inductive coupling. A pair of charging pads, the stationary charging pad and the mobile charging pad, is used for this purpose. A charging pad may incorporate one or more coils and may be underlaid with material that is capable of conducting the magnetic field. As the stationary charging pad and the inverter are combined to form a unit within the stationary part (though they may be arranged at separate locations), no publicly accessible interfaces are required. The stationary part may be embedded in the ground and mounted flush with the road surface, or it may rest on the ground, e.g., for mounting in a garage. The inverter serves to convert the supply voltage and to set the frequency, current and voltage for the magnetic coil(s) of the stationary charging pad. In addition to the mobile charging pad, the mobile part of the charging equipment incorporates the on-board electronics.

In the automotive domain the permanent increase in functionality led to a vast number of electronic control units (ECUs) in today’s cars, but packaging and network bandwidth demands became problematic in the last years. Thus it is vital to integrate more functions per ECU and shift in-car-networking complexity into software. To master this challenge, it is essential to find local and global optimization possibilities, which includes practical software component partitioning strategies while not overlooking the multiplicity of influence factors as well as smart software modules that help to reduce the energy demand wherever possible.

For the next-generation in-vehicle networking infrastructure beyond CAN and FlexRay, the automotive industry has identified Ethernet as a very promising candidate. Ethernet being an IEEE standard and commonly used in consumer and industry domains provides a high re-use factor for components, software and tools. In addition, Ethernet has the bandwidth capability that is required for new driver assistance and infotainment systems, for example. However, to become a success story, solutions for the automotive industry have to be further optimised in terms of scalability, low cost, low power and robustness. The first optimisation steps on the physical layer level have already been taken but more innovation needs to be focused on automotive use cases. This paper discusses new network topologies and components and describes an evolutionary path of Ethernet into automotive applications.

This paper presents the outline of a new system architecture for future electric vehicles. It is designed to simplify the development of advanced assistant functionality (e.g. ADAS) and is based on highly integrated smart actuators. A platform approach is chosen to meet functional as well as non-functional requirements outlined in this paper. A logically centralized platform computer is used as cross-domain runtime environment. All sensors and actuators are accessible from this platform computer. A middleware encapsulates the communication to physical hardware and provides mechanisms for functional safety and security. These mechanisms are fully transparent to vehicle control functions and mask platform failures up to ASIL-D functions. Moreover, platform mechanisms even allow for fail-operational behaviour of these functions and support them in a mixed criticality environment. A key characteristic is “plug-andplay” capability (PnP) for software and hardware, which is supported by OS and middleware even for safety-critical functions. This paper does focus on selected communication mechanisms based on standard Ethernet hardware. Safety assessments are just rudimentary and for the sake of completeness.

With the increasing number and complexity of Advanced Driver Assistance Systems (ADAS) and rising control facility by individual controllable drives in electric vehicles (EV) the reliability of sensor signals becomes more and more important in nowadays vehicles. In order to enhance the safety, the estimation of vehicle states and parameters gets more relevant. In most state of the art functions a vehicle observer secures the correctness of the delivered states. As the performance of observers depends on their input signals a novel plausibility check is implemented. In this paper the checked signals serve the designed adaptive vehicle observer, based on Extended Kalman filtering technique, as input signals. Thus the integrated vehicle functions can control the electric actuators with more precision in order to improve the driving performance and a minimization of energy consumption by an optimal use of the available road traction. The complete system, existing of plausibility check and observer is validated by simulation and will be implemented in an electric vehicle within the EU funded project eFuture.

E/E architectures become more and more complex and thus hamper the introduction of new functions which in turn are essential for the development of electric vehicles. Consequently, new concepts are needed to enable an easy introduction of new technologies along with an interconnected but still manageable architecture. The proposed functional architecture approach aims at a safe operation of electric vehicles with a well defined decision path from the driver and the ADAS functions in the command layer to the actuators of the execution layer. The backbone of this architecture consists of two dedicated decision units. The command decision unit mitigates between requests coming from the driver and the ADAS functions whereas the execution decision unit selects the best actor signals for the current vehicle status. One benefit of this hierarchic approach is the ability to control the validity and the transition between driving modes by a set of rules which can be designed and adjusted to meet the vehicle requirements individually. The concept is not limiting the number of driving modes but is scalable for future applications, different market needs, and vehicle configurations.

Nowadays, the greatest part of the efforts to reduce pollutant emissions is directed toward the hybridization of automotive drive trains. Plug-in Hybrid Electric Vehicle (PHEV) seems to be a good short term solution for replacing the conventional combustion engine propelled vehicles, in order to improve fuel economy and reduce pollution emissions. Such topic has a particular relevance while looking at vehicles that operate in urban environment, like light commercial vehicles used for goods delivering even in limited traffic areas. In order to obtain a wide range, full performance, high efficiency vehicle and, at the same time, reduce pollutant emissions, the most feasible solution, at present, is the PHEV, which combines batteries (that can be charged during the night or enough long stops directly from the electric power grid) that feed electrical drive together with a standard Internal Combustion Engine (ICE). In fact today Full Electric Vehicles can not assure the basic requirements of driving range, performance and load capability needed for a commercial vehicle operating in urban environments, mainly because of the low energy density of actually available batteries. Considering the average daily mission of a commercial vehicle delivering goods in urban environments, PHEV can cover even long distances from the hub to the city centre, exploiting the hybrid driving mode (which can increase the efficiency with respect to standard ICEVs) and then use its pure electric driving range (30-60 km) to deliver goods inside the city centre. Since the PHEV has two on-board engines (electric and endothermic) and two energy storage systems (the electrochemical batteries and the fuel tank), energy control strategies have to be developed and introduced in order to find out the most efficient one. The full energetic model of a Plug-In Hybrid Electric Commercial Vehicle, presented in previous papers [1] and already validated exploiting experimental tests performed on a prototype developed at the Mechanical Engineering Department of Politecnico di Milano, will be used in this paper. It will be used to develop energy flows control strategies able to allow the commercial vehicle to perform its daily mission in hybrid and pure electric driving modes.

The MobiCarin Vehicle Infotainment System addresses the key elements that give OEM systems an advantage over portable devices: seamless integration with the vehicle, hardware control interfaces, and vehicle configuration. The Visteon-based system, currently being developed by the MobicarInfo Consortium, is tailored to the needs of electric vehicle owners, offering access to a set of resources under a single umbrella. These resources include: battery status; upto- date charging station map and station reservation; route planning; real-time information on public transport, and car-sharing. Vehicle configuration and control features include: remote access, in-vehicle and remote AC control, driving mode, power window control, speed and seatbelt notifications, information from temperature and parking sensors, and onboard diagnostics. The system is being developed by the members of the consortium, namely, Critical Software, INTELI, IPN and CEIIA. A functional prototype will be available in late 2012.

Electric vehicles are currently subject of many projects in the areas of research, design and production, but there is also an urgent need for new measurement tools and methods being developed to quantify their parameters and performance, and to assist researchers in their search of improved performance and optimal design decisions. The paper presents the design and implementation of such a measurement system which is devised to address these new demands. Subsequently the work is focused on example data logged from a fully electric vehicle, followed by evaluation of results and analysis.

Detection of moving objects is the fundamental component of both Advanced Driver Assistance Systems (ADAS) and autonomous driving systems in urban environments. This paper proposes a multi-layer laser scan projection approach for motion detection and tracking based on grid mapping. Consecutive grid maps are created to build a temporary dynamic occupancy grid map for each time step. The resulting dynamic grid map is used as an input to a particle filter track-before-detect (TBD) approach. This approach provides robust motion detection in highly dynamic environments. The proposed approach has been evaluated in a real-world scenario using a single moving object and multiple moving objects.

Since some years university and industry research in automotive systems have become strongly focused on cooperative driver assistance systems (Vehicle to X - V2X communication, consisting of Vehicle to Vehicle - V2V and to Infrastructure - V2I). Since the public funded project sim

TD

[1] and the announcements of car manufacturers during the IAA 2011 in Frankfurt / Main it is obvious that such systems will strongly penetrate the automotive market within the next decade [2]. However, such systems with the aim to improve save driving have three basic challenges: First, they must secure a save and stable communication between the desired information providers, second, each partner needs to know his precise position with a time stamp on a global scale and third the provided information needs to be absolutely reliable. Continental provides such a dedicated solution for the sensory needs of V2X systems, the “Motion Information To X Provider” - M2XPro.

Performance testing provides an unbiased way of presenting the benefits of active safety systems. However, some issues must be solved before performance testing can be executed for a system targeting a specific traffic scenario. First of all, the selected scenarios must be motivated; second, a suitable driver model shall be selected; and finally, a generic test target shall be defined. All these issues will be addressed in this paper.

The emergence of Fully Electric Vehicles has sparkled visions of pollution- and noise free cities. However, towards this challenging end, a lot has yet to be accomplished. One of the first priorities should be placed on improving the reliability and energy efficiency of the fully electric vehicles. This paper presents a new Advanced Driver Assistance System that has been implemented, which automatically helps the driver to save more energy while on-trip, by choosing the most energy efficient routes and by providing recommendations whenever necessary. This advanced functionality is based on the collection and exploitation of experiences - through machine learning.

Road friction measurement is an important issue for active safety systems on vehicles; hence knowledge of this key parameter can significantly improve the interventions on vehicle dynamics. This study compares two different on-board sensors for the classification of road conditions with polarised infrared light. Several tests are performed on a dedicated track, with focus on detection of dry or wet surfaces, and the presence of ice or snow. The work shows the capability of both sensors to provide a correct classification. In particular, results indicate how the monitored area, the presence of active illumination and the mounting position influence measurements and response times. It is concluded that both systems classify different road conditions in all cases. Performance of the Road eye system varied from 80 to 90% whereas the camera based IcOR achieved 70-80% accuracy level. Since these are being prototype sensors more development is needed before implemented into advanced safety applications.

This work proposes a smart system to increase road safety. The main idea is to exploit existing technologies and devices, as the smartphone and the existing cellular network, to implement a centralized, real-time, Advanced Driver Assistance System: Each vehicle is equipped with a smartphone that periodically computes and sends the vehicle’s global position and speed through GPRS or UMTS network. A centralized server snaps all running vehicles into digital maps and implements safety algorithms to detect potential dangerous situations. The prediction of a prospective crash generates a warning on the smartphone to alert the driver. This work presents the general hardware and software architecture and the implementation of two use cases. Finally, an evaluation of the critical aspects of the system is provided.

The need of promoting lateral vehicle safety is leading to more and more complex systems. As complexity increases, the evaluation of the potential success of new alternatives becomes a key point in reaching a cost-effective development. A system of four cameras mounted on the side of the vehicle has been suggested. By means of artificial vision, the control unit will be able to monitor the impacting car, and thus take effective measures to prepare the vehicle for the impact, changing the seat set up to aid the passenger and improve passive safety. By means of a simulation model different cases have been simulated varying speeds, locations of impact and studying the period of time on each camera between detection and impact. This simulation model has enabled evaluating the success of the proposed cameras set up.

Based on Kerner’s three-phase theory, we study an algorithm for the generation of traffic jam warming messages from measured GPS and GSM probe vehicle data that have been collected in TomTom’s HD-traffic service both from nomadic devices and vehicle’s embedded systems. We find that the data allows us to reconstruct the structure of congested traffic patterns with a much greater quality of spatiotemporal resolution than has been possible before. It occurs that congested traffic in measured traffic patterns consists of the two traffic phases of Kerner’s three-phase theory, synchronized flow and wide moving jams. The application method distinguishes between the fronts of the congested traffic phases, wide moving jam and synchronized flow. It will be shown that a penetration of about 2% of the total traffic flow is enough to implement a precise traffic jam warning message for navigation systems.

In the context of driver assistance systems lane detection systems are used for lane departure warning and lane centering functions. In some cases, especially in urban scenarios, no lane marks are available and for some circumstances lane marks are not sufficient to assist the driver. For novel urban functions it is necessary to know in which areas the car can operate. This problem requires detecting the free space as a traversable area for vehicles and has to take into account small objects such as curbstones. In this paper we present a real-time road boundary detection for urban areas to realize an easy lane recognition algorithm by using a series hardware stereo camera system. The algorithm is based on dense stereo information.

We propose a system design for preventive traffic safety in general intersection situations involving all present traffic participants (vehicles and vulnerable road users) in the context of their environment and traffic rules. It exploits the developed overall probabilistic framework for modeling and analysis of intersection situations under uncertainties in the scene, in measured data or in communicated information. It proposes OOBN modeling for the cognitive assessment of potential and real danger in intersection situations and presents schematically an algorithm for multistage cognitive situation assessment. A concept for the interaction between situation assessment and the proposed Proactive coaching Safety Assistance System (PaSAS) is outlined. The assessment of danger in a situation development serves as a filter for the output and intensity of HMI-signals for directing driver’s attention to essentials.

The goals of the project NAV-CAR are both to enable lane sensitive navigation for cars on highways and to increase robustness for high precision positioning in specific environments such as urban canyons and alpine regions where satellite based navigation systems may fail. The challenge of the project is the technical realization with a reasonable ratio of accuracy vs. costs, which is met by using sensor fusion technologies and stepwise integration of car specific data with GPS, which was implemented via an on-board unit (OBU) with CAN-bus interface. The approach was validated by test drives on urban (Vienna, A 23) as well as alpine highways (Brenner, A11/A12). Precise lane-specific trajectory reference data were derived from test drives with a special surveillance truck RoadStar. To estimate the potential impact of Galileo services as compared to existing GPS a simulation with data input from test drives in an alpine region was performed. The generation and inclusion of enhanced maps as a further option was evaluated.

Vehicle re-identification gives access to two essential data for traffic management: travel times and origin-destination matrices. This paper aims to evaluate the performances of a vehicle re-identification method based on Euclidean distances between vehicle “magnetic signatures” measured with several three-axis magnetic sensors. These performances are compared to the ones achieved by a single sensor and the three-dimensional (3D) Dynamic Time Warping algorithm. Moreover, the effects of a change in the vehicle orientation or in its lateral position are studied. On a data base of signatures from 25 different vehicles, the best results are obtained with the 3D Euclidean distance: 100% of the pairs of signatures are correctly re-identified without any false alarm if the vehicle keeps the same orientation and 90% if the vehicle orientation changes. The influence of the vehicle orientation to the magnetic North on the signature is therefore limited. However, the performances fall when the vehicle lateral position shifts.

Cost-efficient sensor solutions are of high interest for automotive safety applications, in order to increase the use of sensor-based active safety functions and therefore improve traffic safety. In the European collaboration project Minifaros, a cost-efficient laser scanner is being developed. Particularly for heavy vehicles, cost-efficient sensors are of interest to observe objects in the close vicinity of the host vehicle. In this contribution, we will first describe the need and requirements for low-cost sensors and particularly discuss the special needs for truck applications of this sensor. Then, the target and benchmark applications for the cost-efficient laser scanner being developed in Minifaros will be described, consisting of vulnerable road user protection functions and low-speed Adaptive Cruise Control.

In today’s high class vehicles, Night Vision and Pedestrian Detection Systems take benefit of passive thermal detection based on the used Far Infrared (FIR) Imaging Sensor. Formally developed since the 1980’s for night vision system used in military application, the main industrial technologies are currently producing 2D array chip formed by MEM’s microbolometer integrated into vacuum package. Improvements made by ULIS over the last 10 years on microbolometers made from amorphous silicon enable today the use of FIR imaging sensors in highly demanding commercial applications such as automotive market. The high level of accumulated expertise by ULIS and CEA/LETI follows the continuous technology development roadmap, as detection material improvement, pixel pitch reduction, vacuum package technology breakthroughs, or readout integrated circuit (ROIC) on-chip innovation. The new ULIS product 1/4. VGA format based on 17

μ

m pixel-pitch, low cost vacuum package and improved ROIC enables the improvement of Night Vision and Pedestrian Detection Systems, by simplifying system design, and reducing calibration process and production time, offering high performances compatible with hundreds meters of detection range even in day or night conditions. This paper describes the technology roadmap and product improvements regarding automotive expectations.

This paper presents an integrated receiver channel and an integrated time-to-digital (TDC) converter fabricated in a 0.35

μ

m SiGe BiCMOS and in 0.35

μ

m CMOS technologies, respectively, that give the required performance for a pulsed time-of-flight (TOF) laser radar to be used in a laser scanner in automotive applications. The receiver-TDC chip set is capable to measure the positions and widths of three separate successive timing pulses with sub-ns level precision in a wide dynamic amplitude range of more than 1:10.000.

Low cost laser scanners for environment perception are a need to facilitate ADAS integration into all vehicle segments. To fulfill the need for mass-producible compact low cost laser range sensors MEMS mirrors in combination with replicable low cost plastic optics are expected to be suitable components. This paper describes concept, design, fabrication and first measurement results of a compact omnidirectional scanning system based on an omnidirectional lens and a biaxial large aperture tripod MEMS mirror. A hermetic vacuum wafer level packaging process of the resonant MEMS mirror is essential to meet automotive requirements and to achieve the required large total optical scan angles of 60 degrees in both scan axes.

The DTF Data Time Flow Simulator is developed at the AIT Austrian Institute of Technology in the course of the EU ARTEMIS Project POLLUX which is related to the design of electronic control systems for the next generation of electric vehicles. An important element of a vehicle is the communication architecture for the electronic control system. The DTF is a model based development approach, based on a modular assembly system for incremental design and analysis of electronic control systems. A current application of the DTF is related to the design and performance analysis of communication architectures for the electronic control system of an electric vehicle. This paper introduces a generic approach that shall enable companies to design and assess their control systems without the need to provide corporate know-how to third parties like tool developers.

In the past 15-20 years, sensors have grown organically and reached relatively stable penetration rates with very low growth, at least in the mature automotive markets. Any new stimulus therefore comes from the adoption of safety and basic powertrain sensors and regulations and mandates that force adoption to full penetration in different regions. The current paper provides a 5-year snapshot of the market opportunity for safety and powertrain applications for the silicon sensors based on Micro Electro Mechanical System (MEMS) technology and also magnetic sensors used in position, rotation and angle measurements, and looks at the underlying drivers in detail.