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In order to achieve high customer satisfaction and to avoid high warranty costs caused by component failures of the power-train of hybrid electric vehicles (HEV), car manufacturers have to optimize the dimensioning of these elements. Hence, it is obligatory for them to gain knowledge about the different types of vehicle usage being predominant all over the world. Therefore, in this paper we present a Data Mining system that employs a Random Forest (RF) based dissimilarity measure in the dimensionality reduction technique t-Distributed Stochastic Neighbor Embedding (t-SNE) to automatically identify and visualize different types of vehicle usage by applying these methods to aggregated logged on-board data, i.e., load spectrum data. This kind of data is calculated and recorded directly on the control units of the vehicles and consists of aggregated numerical data, like the histogram of the velocity signal or the traveled distance of a vehicle.

There is a growing need for life-cycle data – so-called collectives – when developing components like elastomer engine mounts. Current standardized extreme load cases are not sufficient for establishing such collectives. Supplementing the use of endurance testing data, a prediction methodology for component temperature collectives utilizing existing 3D CFD simulation models is presented. The method uses support points to approximate the full collective. Each support point is defined by a component temperature and a position on the time axis of the collective. Since it is the only currently available source for component temperature data, endurance testing data is used to develop the new method. The component temperature range in this data set is divided in temperature bands. Groups of driving states are determined which are each representative of an individual band. Each of the resulting four driving state spaces is condensed into a substitute load case.

Air spring systems gain more and more popularity in the automotive industry and with the ever growing demand for comfort nowadays they are almost inevitable. Some significant advantages over conventional steel springs are appealing for commercial vehicles as well as for the modern passenger vehicles in the luxury class. Current production air spring systems exist in combination with hydraulic shock absorbers (integrated or resolved). An alternative is to use the medium air not only as a spring but also as a damper: a so-called air spring air damper. Air spring air dampers are force elements which could be a great step for the chassis technology due to their functionality (frequency selectivity, load levelling, load independent vibration behaviour, load dependent damping). Some of their design which avoid dynamic seals by the using of rubber bellows contribute to a better ride comfort.

Due to the diversity of Heavy Duty Vehicles (HDV), the European CO2 and fuel consumption monitoring methodology for HDVs will be based on a combination of component testing and vehicle simulation. In this context, one of the key input parameters that need to be accurately defined for achieving a representative and accurate fuel consumption simulation is the vehicle's aerodynamic drag. A highly repeatable, accurate and sensitive measurement methodology was needed, in order to capture small differences in the aerodynamic characteristics of different vehicle bodies. A measurement methodology is proposed which is based on constant speed measurements on a test track, the use of torque measurement systems and wind speed measurement. In order to support the development and evaluation of the proposed approach, a series of experiments were conducted on 2 different trucks, a Daimler 40 ton truck with a semi-trailer and a DAF 18 ton rigid truck.

Securing the desired strength and durability characteristics of suspension components is one of the most important topics in the development of commercial vehicles because these components undergo multiaxial variable amplitude loading. Leaf springs are essential for the suspension systems of trucks and they are considered as security relevant components in the product development phase. In order to guide the engineers in the design and testing department, a simulation method is developed as explained by Bakir et al. in a recently published SAE paper [1]. The main aim of the present study is to illustrate the validation of this simulation method for the durability of leaf springs based on the results from testing and measurements. In order to verify this CAE Method, the calculated stresses on the leaf springs are compared with the results of strain gage measurements and the fatigue failures of leaf springs are correlated with the calculated damage values.

Collective life-cycle data is needed when developing components like elastomer suspension mounts. Life-time prediction is only possible using thermal load frequency distributions. In addition to current extreme load cases, the Idle Load Case is examined at Mercedes-Benz Car Group as a collective load case for Vehicle Thermal Management (VTM) numerical simulations in early development stages. It combines validation opportunities for HVAC, cooling and transmission requirements in hot-country-type ambient conditions. Experiments in climatic wind tunnels and coupled 3D CFD and heat transfer simulations of the Idle Load Case have been performed. Measurements show steady conditions at the end of the load case. Decoupling of the torque converter, changes in ambient temperature and the technical implementation of a wind barrier for still air conditions exhibit influence on component-level results. Solar load, however, does not significantly change the examined component temperatures.

An overview of Daimler?s progression to advance powertrain technology in a growth industry shows many different solutions to improvement in transportation. Daimler continues to make breakthroughs in technology development and application building on 125 years of automotive development. Optimization of current powertrains will enable a significant gain in CO2/mi reductions, that dependent on product mix can be augmented with additional technologies. There is however no bypass to some form of electrification, enabling efficiency gains and alternative forms of power supply. Development of hybrid powertrains continues in an established manner and enhanced development of further electrified powertrains are in development. Organizationally and technically, significant skills and adjustments need to continue to be undertaken enabling OEMs and in particular the supply base to develop optimized solutions efficiently. The outlook is bright for novel component development and innovation.

Since 2013 the new Daimler Aeroacoustic Wind Tunnel (AAWT) is in operation at the Mercedes-Benz Technology Center in Sindelfingen, Germany. This construction was the second stage of a wind tunnel center project, which was launched in 2007 and started with the climatic wind tunnels including workshop and office areas. The AAWT features a test facility for full-scale cars and vans with a nozzle exit area of 28 m2, a five-belt system, and underfloor balance to measure forces with best possible road simulation. With a remarkable low background noise level of the wind tunnel, vehicle acoustics can be investigated under excellent conditions using high-performance measurement systems. An overview is given about the building and the design features of the wind tunnel layout. The aerodynamic and aeroacoustic properties are summarized. During the first years of operation, further improvements regarding the wind tunnel background noise and vehicle handling were made.

The TOP TIERTM Diesel fuel standard was first established in 2017 to promote better fuel quality in marketplace to address the needs of diesel engines. It provides an automotive recommended fuel specification to be used in tandem with regional diesel fuel specifications or regulations. This fuel standard was developed by TOP TIERTM Diesel Original Equipment Manufacturer (OEM) sponsors made up of representatives of diesel auto and engine manufacturers. This performance specification developed after two years of discussions with various stakeholders such as individual OEMs, members of Truck and Engine Manufacturers Association (EMA), fuel additive companies, as well as fuel producers and marketers. This paper reviews the major aspects of the development of the TOP TIERTM Diesel program including implementation and market adoption challenges.

The overall efficiency of hybrid electric vehicles largely depends on the design and application of its energy management system (EMS). Despite the load coordination when operating the system in a hybrid mode, the EMS accounts for state changes between the different driving modes. Whether a transition between pure electric driving and internal combustion engine (ICE) powered driving is beneficial depends, among others, on the respective operation point, the route ahead as well as on the energetic expense for the engine start itself. The latter results from a complex interaction of the powertrain components and has a tremendous impact on the efficiency and quality of EMSs. Optimization based methods such as dynamic programming serve as benchmark for the design process of rule based control strategies. In case no energetic expenses are assigned to a state change, the resulting EMS suffers from being sub-optimal regarding the fuel consumption.

Aerodynamic design and thermal management are some of the most important tasks when developing new concepts for the flow around tractor-trailers. Today, both experimental and numerical studies are an integral part of the aerodynamic and thermal design processes. A variety of studies have been conducted how the aerodynamic design reduces the drag coefficient for fuel efficiency as well as for the construction of radiators to provide cooling on tractor-trailers. However, only a few studies cover the combined effect of the aerodynamic and thermal design on the air temperature of the under hood flow [8, 13, 16, 17, 20]. The objective of this study is to analyze the heat transfer through forced convection for a scaled Cab-over-Engine (CoE) tractor-trailer model with under hood flow. Different design concepts are compared to provide low under hood air temperature and efficient cooling of the sub components.

This paper summarizes a common project of Mercedes-Benz and FKFS (Research Institute of Automotive Engineering) to apply numerical methods to thermal soak issues in a very early stage of the development phase of a new car. “Thermal soak” results from driving the vehicle at high load followed by shutting off the engine and a cool down phase. After stopping, the underhood flow is only driven by natural convection. The thermal soak behaviour is discussed in principal and the numerical challenges are summarized. Four different issues are identified: the need for a transient computation including transient thermal load pattern, a method to compute natural convection in the underhood after the shutdown of the engine, the complex geometry and the lack of a single computational program to consider all three modes of heat transfer, which results in a coupled numerical approach.

Safety-critical embedded software has to satisfy stringent quality requirements. All contemporary safety standards require evidence that no data races and no critical run-time errors occur, such as invalid pointer accesses, buffer overflows, or arithmetic overflows. Such errors can cause software crashes, invalidate separation mechanisms in mixed-criticality software, and are a frequent cause of errors in concurrent and multi-core applications. The static analyzer Astrée has been extended to soundly and automatically analyze concurrent software. This novel extension employs a scalable abstraction which covers all possible thread interleavings, and reports all potential run-time errors, data races, deadlocks, and lock/unlock problems. When the analyzer does not report any alarm, the program is proven free from those classes of errors. Dedicated support for ARINC 653 and OSEK/AUTOSAR enables a fully automatic OS-aware analysis.

The number of full electric and hybrid electric vehicles is rapidly growing [1][2][3]. The new technologies accompanying this trend are increasingly becoming a focal point of interest for rescue services. There is much uncertainty about the right techniques to free trapped occupants after an accident. The same applies to vehicle fires. Can car fires involving vehicles with a lithium ion traction battery be handled in the same way as conventional vehicle fires? Is water the right extinguishing agent? Is there a risk of explosion? There are many unanswered questions surrounding the topic of electric vehicle safety. The lack of information is a breeding ground for rumours, misinformation and superficial knowledge. Discussions on various internet platforms further this trend. Tests were conducted on three lithium ion traction batteries, which were fuel-fired until burning on their own. The batteries were then extinguished with water, a surfactant and a gelling agent.

The reduction of fuel consumption as well as the rising demands of customers regarding a vehicle’s driving dynamic and the legislator’s continually rising demands are a current issue in vehicle development. Hybrid vehicles offer a possibility to rise to this challenge. Realistic driving cycles are of utmost importance for the calibration of a hybrid vehicle’s operational strategy. Deriving replacement speed cycles from extensive customer data sets seems to be an approach for solving these problems. The contribution at hand describes the derivation of replacement cycles by using stochastic models, probabilistic (weighted) drawings and a combinatorial optimisation. The novelty value is that the characteristic influences of all drivers are being considered in the generation due to the stochastic modelling.

In the next 20 years the share of small electric vehicles (SEVs) will increase especially in urban areas. SEVs show distinctive design differences compared to traditional vehicles. Thus the consequences of impacts of SEVs with vulnerable road users (VRUs) and other vehicles will be different from traditional collisions. No assessment concerning vehicle safety is defined for vehicles within European L7e category currently. Focus of the elaborated methodology is to define appropriate test scenarios for this vehicle category to be used within a virtual tool chain. A virtual tool chain has to be defined for the realization of a guideline of virtual certification. The derivation and development of new test conditions for SEVs are described and are the main focus of this work. As key methodology a prospective methodical analysis under consideration of future aspects like pre-crash safety systems is applied.

A wide variety of applications such as driver assistant and energy management systems are researched and developed in virtual test environments. The safe testing of the applications in early stages is based on parameterizable and reproducible simulations of different driving scenarios. One possibility is modeling the microscopic driving behavior to simulate the longitudinal vehicle dynamics of individual vehicles. The currently used driver models are characterized by a conflict regarding comprehensibility, accuracy and calibration effort. Due to the importance for further analyses this conflict of interests is addressed by the presentation of a new microscopic driver model in this paper. The proposed driver model stores measured driving behaviors with its statistical distributions in maps. Thereby, the driving task is divided into free flow, braking in front of stops and following vehicles ahead. This makes it possible to display the driving behavior in its entirety.

In order to offer a wide range of driving experiences to their customers, original equipment manufacturers implement different driving programs. The driver is capable of manually switching between these programs which alter drivability parameters in the engine control unit. As a result, acceleration forces and gradients are modified, changing the perceived driving experience. Nowadays, drivability is calibrated iteratively through road testing. Hence, the resulting set of parameters incorporated within the engine control unit is strongly dependent on the individual sentiments and decisions of the test engineers. It is shown, that implementing a set of objective criteria offers a way to reduce the influences of personal preferences and sentiments in the drivability calibration process. In combination with the expertise of the test engineers, the desired vehicle behavior can be formalized into a transient set point sequence to give final shape to the acceleration behavior.

Todays tuning of hydraulic vehicle shock absorbers is mainly an empirical iterative process performed in time-consuming and expensive ride tests, whereas the majority of damper simulation models used for investigating vehicle ride behavior is based on an abstract parameterization. For the manufacturing of automotive dampers, however, the valve code is essential. Minor changes in the valve code describing the shim stack in the hydraulic valves may have a noticeable impact on the damper characteristics, while the physical effects are still not sufficiently understood. Therefore, the paper presents a detailed physics-based structural model to investigate the pressure-deflection behavior of shim stacks and the influence of specific discs in the stack. The model includes a variety of effects like friction and preload, and is capable to predict the damper characteristics.

Driver assistance systems (e.g. the emergency brake assist Active Brake Assist2, or ABA2 for short, in the Mercedes-Benz Actros) are becoming increasingly common in heavy-duty commercial vehicles. Due to the close interconnection with drivetrain and suspension control systems, the integration and validation of the functions make the most exacting demands on processes and tools involved in mechatronics development. Presenter Thomas Bardelang, Daimler AG