Search Results

The BMW Group has introduced electric cars to the market with the MINI E already in 2009. The next step will be the launch of the BMW ActiveE in 2011, followed by the revolutionary Mega City Vehicle in 2013. The presentation will explain the BMW Group strategy for implementing sustainable mobility. A focus will be emobility, the use of carbon fiber and the holistic sustainability approach of BMW Group?s project i. Reference will be made to the research results of the MINI E projects in the US and in Europe. Presenter Andreas Klugescheid, BMW AG

The reliability of electronic components is of increasing importance for further progress towards automated driving. Thermal aging processes such as electromigration is one factor that can negatively affect the reliability of electronics. The resulting failures depend on the thermal load of the components within the vehicle lifetime - called temperature collective - which is described by the temperature frequency distribution of the components. At present, endurance testing data are used to examine the temperature collective for electronic components in the late development stage. The use of numerical simulation tools within Vehicle Thermal Management (VTM) enables lifetime thermal prediction in the early development stage, but also represents challenges for the current VTM processes [1, 2]. Due to the changing focus from the underhood to numerous electronic compartments in vehicles, the number of simulation models has steadily increased.

Each component of a drive train generates waste heat due to its limited efficiency. This waste heat is usually released to an air flow guided through one or more heat exchangers. So, the realized cooling air volume flow is one important characteristic value during the vehicle development process. This paper presents some of the available techniques for the measurement of cooling air volume flow in the vehicle during the different stages of an aerodynamic development process in model scale and full scale. Additionally, it provides suggestions when comparing these experimental values to CFD results.

Today's automotive software integration is a static process. Hardware and software form a fixed package and thus hinder the integration of new electric and electronic features once the specification has been completed. Usually software components assigned to an ECU cannot be easily transferred to other devices after they have been deployed. The main reasons are high system configuration and integration complexity, although shifting functions from one to another ECU is a feature which is generally supported by AUTOSAR. The concept of a Virtual Functional Bus allows a strict separation between applications and infrastructure and avoids source code modifications. But still further tooling is needed to reconfigure the AUTOSAR Basic Software (BSW). Other challenges for AUTOSAR are mixed integrity, versioning and multi-core support. The upcoming BMW E/E-domain oriented architecture will require all these features to be scalable across all vehicle model ranges.

This paper presents an autonomous cruise control for battery electric vehicles. The presented approach is based on the usage of predictive route data which is extracted out of a digital map and a wide range radar system in order to capture vehicles in front. By using the predictive route data and the information of the radar system, the autonomous cruise control can control the vehicle's speed over a wide range of driving situations without any driver interaction. The main aim of the presented autonomous cruise control is to optimize the battery electric vehicle's energy consumption. The main idea is to use predictive route data in order to calculate a consumption optimal vehicle speed trajectory by means of online optimization. The benefits of the autonomous cruise control are shown by means of real test drives and measured data evaluation.

In use cars often drive through the wakes of other vehicles. It has long been appreciated that this imposes a fluctuating onset flow which can excite a structural response in vehicle panels, particularly the bonnet. This structure must be designed to be robust to such excitation to guarantee structural integrity and maintain customer expectations of quality. As we move towards autonomous vehicles and exploit platoons for drag reduction, this onset flow condition merits further attention. The work reported here comprises both measurements and simulation capturing the unsteady pressure distribution over the bonnet of an SUV following a similar vehicle at high speed and in relatively close proximity. Measurements were taken during track testing and include 48 static measurement locations distributed over the bonnet where the unsteady static pressures were recorded.

The results of previous Life Cycle Assessments indicate the ecological dominance of the vehicle's use phase compared to its production and recycling phase. Particularly the so-called weight-induced fuel saving coefficients point out the great spectrum (0.15 to 1.0 l/(100 kg · 100 km)) that affects the total result of the LCA significantly. The objective of this article, therefore, is to derive a physical based, i.e. scientific chargeable and practical approved, concept to determine the significant parameters of a vehicle's use phase for the Life Cycle Inventory. It turns out that - besides the aerodynamic and rolling resistance parameters and the efficiencies of the power train - the vehicle's weight, the rear axle's transmission ratio and the driven velocity profile have an important influence on a vehicle's fuel consumption.

The hybrid power train technology offers various prospects to optimize the engine efficiency in order to minimize the CO₂ emissions of an internal-combustion-engine-powered vehicle. Today different types of hybrid architectures like parallel, serial, power split or through-the-road concepts are commonly known. To achieve lowest fuel consumption the following hybrid electric vehicle drive modes can be used: Start/Stop, pure electric/thermal driving, recuperation of brake energy and the hybrid mode. The high complexity of the interaction between those power sources requires an extensive investigation to determine the optimal configuration of a natural-gas-powered SI engine within a parallel hybrid power train. Therefore, a turbocharged 1.0-liter 3-cylinder CNG engine was analyzed on the test bench. Using an optimized combustion strategy, the engine was operated at stoichiometric and lean air/fuel ratio applying both high- and low-pressure EGR.

This paper introduces a driving-torque measurement method for the determination of vehicle road load and its components. To increase the accuracy, the torque measurements are combined with rolling resistance measurements performed with a specially developed trailer. This method is a strictly experimental approach and does not use any mathematical models. The experimental techniques are described as well as the proceedings to compare test stand and road measurements. The results that are shown prove that this method is suitable for the investigation of single road load components. Furthermore, the comparison of different rolling resistance measurement devices shows the potential of the measurement trailer and the necessity to perform rolling resistance measurements on real road surfaces and not solely on test stands.

In this paper the development approach and the results of numerical and experimental investigations on homogeneous charge compression ignition in a free piston engine are presented. The Free Piston Linear Generator (FPLG) is a new type of internal combustion engine designed for the application in a hybrid electric vehicle. The highly integrated system consists of a two-stroke combustion unit, a linear generator, and a mass-variable gas spring. These three subsystems are arranged longitudinally in a double piston configuration. The system oscillates linearly between the combustion chamber and the gas spring, while electrical energy is extracted by the centrally arranged linear generator. The mass-variable gas spring is used as intermediate energy storage between the downstroke and upstroke. Due to this arrangement piston stroke and compression ratio are no longer determined by a mechanical system.

Air conditioning acoustics have become of paramount importance in electric vehicles, where noise from electromechanical components is no longer masked by the presence of the internal combustion engine. In a car HVAC systems, the coolant compressor is one of the most important sources in terms of vibration and noise generation. The paper, the generated structural noise is studied in detail on a prototype installation, and the noise transmission and propagation mechanisms are analyzed and discussed. Through ”in situ” measurements and virtual point transformation, the rotor unbalance forces and torque acting within the component are identified. The dynamic properties of the rubber mounts, installed between the compressor and its support, are identified thanks to matrix inversion methods. To assess the quality of the proposed procedure, the synthesized sound pressure level is compared with experimental SPL measurements in different operational conditions.

It is particularly easy to get tunnel vision as a domain expert, and focus only on the improvements one could provide in their area of expertise. To make matters worse, many Original Equipment Manufacturers (OEMs) are silo-ed by domain of expertise, unconsciously promoting this single mindedness in design. Unfortunately, the successful and profitable development of a vehicle is dependent on the delicate balance of performance across many domains, involving multiple physics and departments. Taking for instance the design of a Heating, Ventilation & Air Conditioning (HVAC) system, the device’s primary function is to control the climate system in vehicle cabins, and more importantly to make sure that critical areas on the windshield can be defrosted in cold weather conditions within regulation time. With the advent of electric and autonomous vehicles, further importance is now also placed on the energy efficiency of the HVAC, and its noise.

Increasing demand for utilities like navigation systems or user-defined electronic phonebooks on one hand and sophisticated engine and gear controls on the other hand leads to growing bus load between distributed local control units. This paper shows the benefits and the characteristics of various state of the art data-compression algorithms and their impact on typical automotive multiplex dataclasses. The evaluation and optimization of promising algorithms can be done via a proposed “communications prototyping”-approach. The hardware/software components of such a rapid prototyping package are outlined. Finally, first performance results of suitable data-compression measures are presented.

In this paper, a serial/parallel hybrid electric vehicle with a 17 kWh battery and 400 V voltage level is simulated. The vehicle is a C-segment vehicle, which has optimized driving resistances. It also has an external recharge possibility, which enables fully electric driving. The vehicle uses an Otto-engine concept as well as two electric motors. One motor is a permanent magnet synchronous motor and can be used as traction motor or generator, the other one is an induction motor used as main traction motor for the vehicle. The vehicle uses a 2-speed gearbox, where the electric motors are mounted in P2-configuration. To reach optimal results for the fuel consumption, an operating strategy based on the Equivalent Consumption Minimization Strategy (ECMS) is introduced and implemented in the vehicle simulation.

BMW has introduced new test stands for noise measurements on passenger cars and motorcycles. Information is given on room conditions, machinery equipment, sound levels, frequency ranges and types of measurement. The semi-anechoic room is designed for measuring the sound distribution emitted by a single vehicle. Road influence is simulated by a reflecting floor and a roller-dynamometer. The free field sound distribution in terms of distance and direction is measured in the anechoic room. This room has high-precision installations for sound source identification and noise mapping. The reverberation room serves to measure sound power emitted by the test object. Its second purpose is to subject the bodywork to a high-power external sound source and to measure the sound-deadening effect of the passenger compartment. In conclusion, the presentation provides reports on the initial experience with these test facilities.

With the law on autonomous driving and the associated ordinance, it has been possible in Germany since June 2022 to grant operating permission to vehicles with automated driving function and to admit them to road traffic. For public transport, automated shuttle buses offer the opportunity to maintain the existing service despite a shortage of personnel and to close gaps in supply. The safety of vehicle occupants, other road users and third parties is a key concern in the operation of automated shuttle buses. As part of the project RABus “Real laboratory for automated bus operation in public transport in urban and rural areas”, which is funded by the Ministry of Transport Baden-Württemberg, the operational reliability of automated shuttle buses (SAE Level 4) in public transport is being scientifically investigated. In the implementation of automated driving, obstacle detection/avoidance is a safety-critical driving function.

In this work, a novel approach is introduced comprising a combination of unsupervised machine learning (ML) scheme and charging energy management of electric vehicles (EV). The main goal of this implementation is to reduce the load peak of charging EV’s, which are regular users of electric vehicle supply equipment (EVSE) of a certain building and, at the same time, to meet their electric and behavioral demands. The unsupervised ML considers certain features within the charging profiles in addition to the behavioral characteristics of the EV based on its intended use. Moreover, these features are extracted from large sets of history measurement data of the EVSE, which are stored in the data bank. The ML categorizes the EVs within certain clusters having defined specifications.

Within the last years, the number of electric vehicles in Europe is increasing faster than the number of charging stations. Based on this, the reliability of the charging process takes on greater significance. The communication between the electric vehicle (EV) and their charging station is a prerequisite to transfer the charging power. Using a universal charging communication test system allows an observation of the whole charging communication according to ISO 15118 and IEC 61851 standards. It is important to know whether the communication between the EV and the charging station functions accordingly, in order to ensure functionality. Furthermore, tolerances must comply with the standard. In a first step, the basic communication according to IEC 61851 is considered. Preliminary investigations of the pulse width modulation (PWM) signal have shown that some EVs are tolerant of the standards.

In April 1996 the European Project „Electric Vehicle Fleet Demonstration with advanced Batteries” has been started with financial support of the European Commission. Sixteen electric vehicles equipped with ZEBRA batteries have been built up as prototypes and are now operating in five major European cities. Today, after 1½ years of fleet operation the fleet of 10 OPEL Astra Impuls has covered a mileage of more than 275.000 km and the project can be evaluated sufficiently exact to extrapolate the project results. Energy consumption structures, mobility structures (daily trip length) and user acceptance have been analyzed and will be discussed in detail.

Due to their high energy density, power density, and durability, lithium-ion (Li-ion) batteries are rapidly becoming the most popular energy storage method for electric vehicles. Difficulty arises in accurately estimating the amount of left capacity in the battery during operation time, commonly known as battery state of charge (SOC). This paper presents a comparative study between six different Equivalent Circuit Li-ion battery models and two different state of charge (SOC) estimation strategies. The Battery models cover the state-of-the-art of Equivalent Circuit models discussed in literature. The Li-ion battery SOC is estimated using non-linear estimation strategies i.e. Extended Kalman filter (EKF) and the Smooth Variable Structure Filter (SVSF). The models and the state of charge estimation strategies are compared against simulation data obtained from AVL CRUISE software.