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Meet us in person

We are always glad to answer any questions face-to-face that you may have on research at Bosch. So feel free to meet up with Bosch Research experts (on-site or virtual) at one of our events, at trade fairs, or after a presentation in 2021.

University of Stuttgart: Lecture: “Automotive radar systems for autonomous driving”

since autumn 2020, virtual event


- Basics of autonomous driving and active environment sensors
- Radar fundamentals
- Radar types
- Automotive radar
- Radar signal processing
- Detection theory for radar
- Angular estimation and imaging
- MIMO radar
- Novel radar modulations
- Synthetic aperture radar
- Clustering und Tracking

German Hydrogen General Assembly

January 26-27, 2021, Berlin, Germany

Fuel cells for mobility: HyPerformance – component kit for mobile fuel cell systems, Dr Helerson Kemmer

Design, Automation and Test in Europe Conference (DATE 2021)

February 1-5, 2021, virtual conference

Organizer of Special Initiative on Autonomous System Design (ASD)

University of Southern California, department of Aerospace and Mechanical Engineering, Spring 2021 seminars

February 24, 2021, virtual event


Overview of Giovanna Bucci's published work on mesoscale modeling of energy materials and for DNA-sequencing applications

MBMV 2021 – 24th workshop on methods and description languages for the modeling and verification of circuits and systems.

March 18-19, 2021, virtual conference


Simulating Vehicle Computer Systems – driven by new functionality and applications (like automated driving and vehicle-to-X-connectvity), the automotive industry is introducing centralized electric/electronic architectures featuring powerful vehicle computers. This poses new challenges for the development process and particularly also for the HW/SW integration and validation. This talk gives insights into current approaches and upcoming research challenges for modelling and simulation of automotive applications.

Deutsche Jungforscher Netzwerk juFORUM e.V. conference

March 26-28, 2021, virtual conference

1) Microfluidics simulations in PEM fuel cells
2) Automated driving with infrastructure support
3) (Partly) automated risk assessment and security approval of versatile production machines
4) Adaptive machine intelligence for robot assembly

Knowledge Graph Conference

May 3-6, 2021, virtual conference

Talk about knowledge-infused learning for autonomous driving by Cory Henson

2021 IEEE International Conference on Prognostics and Health Management (ICPHM 2021)

June 7-9, 2021, Detroit, USA (virtual event)


Automated Dynamic Safety Evaluation of Generic Fail-Operational Mechatronic Systems

The increasing complexity of connected and distributed mechatronic systems developed for safety-critical applications, as e.g. a powertrain of automated vehicles, makes their dependability evaluation a challenging task. Moreover, precise statements about the dependability metrics are of high interest for architectural decisions in the early stages of the design process. System dynamics, possible fault combinations as well as the sequence, duration and impact of various faults and the associated system states must be considered for a realistic evaluation and quantification of the failure behavior. In order to optimize the design of generic mechatronic systems at different abstraction levels and with different component characteristics, this paper examines a method to analytically quantify the stochastic behavior of a system. The proposed approach enables to significantly increase the computational efficiency of the safety analysis of generic fail-operational mechatronic systems without loss in accuracy by automating the dynamic evaluation of convolutional integrals. The application of the proposed safety analysis is demonstrated using an example system with dynamic redundancy.

Inter - Noise 2021: 50th International Congress and Exposition on Noise Control Engineering

August 1-5, 2021, Washington DC, USA

Experimental investigation on acoustics and efficiency of rotor configurations for electric aerial vehicles

Aerial vehicles based on distributed electric propulsion systems have gained great interest. Their rotors, however, create loud and annoying sound, which impends market success. Variations in rotor configuration can be observed on emerging concepts, whereby the main varied parameters are blade size, number of blades and blade distribution.

The focus of this paper is to identify how these parameters can be chosen to optimize eciency and acoustics, including psychoacoustic metrics of single rotors while hovering. Results from experimental investigations done in a hover-test-bench are presented. Rectangular, symmetric blades are used. Experiments are done varying blade size (radius 61 mm to 126 mm), number of blades (2 to 8) and blade distribution (equal and unequal angles). Acoustic measurements are analyzed regarding microphone position, sound pressure level, spectral characteristics and psychoacoustic metrics.

Results show that variations in blade size, number of blades and blade distribution can improve efficiency and acoustics. Influence of these parameters on the acoustic signature at constant thrust is discussed. Conclusions for optimized rotor design at aerial vehicles are derived and supplemented by resulting boundary conditions like assembly space and weight.

9th International Symposium on Development Methodology

November 9-10, 2021, Wiesbaden, Germany

Verification of electric axle simulation models via a coupled eAxle-in-the-loop approach

The rapid change from internal combustion engines to electric drives in the automotive industry requires efficient development processes. The early phase of product development is increasingly accompanied by modelling and simulation of the complete vehicle. Extensive tests and optimizations on test benches follow. In this work, both the simulative and the test-based methods are improved by coupling a complete vehicle model with a test bench for electric drivetrains. Such an eDrive-in-the-Loop system enables realistic tests on the drive train test bench through the integration of the complete vehicle and the environment models. The modelling of electric drive trains is also associated with numerous uncertainties due to complex physical relationships. Particularly, thermal effects can only be represented in a very simplified manner in a system simulation. Outsourcing the drive train to the test bench can therefore significantly improve the simulation results.

In contrast to conventional hardware-in-the-loop systems, an object-oriented simulation model is used in this work. This enables a high level of detail and good understanding of the model structure but cannot be carried out on a real-time computer. Therefore, the connection to the test bench is established via a co-simulation with an integrated real-time interface. This requires a middleware that coordinates the data exchange between the simulation and the test bench in real time. With this approach, hardly any changes need to be made in the vehicle model. The co-simulation can be run on a Windows notebook, which means that no additional hardware is required.

With adequate coupling settings in the co-simulation middleware, a stable, accurate and real-time-capable test environment can be assured. The simulation model of the test vehicle can be modified very efficiently, thus allowing a fast analysis of effects on the electric axle due to changes on the (simulated) vehicle system level.

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