Michael Stolz

Fixed step clutch modeling and simulation for automotive real-time applications

Efficient coordination of actuating elements is an important challenge for modern automotive control units in order to deliver the requested torque for propulsion during all driving conditions. Model-based approaches have large potential to deal with the growing complexity. The need for real-time execution leads to fixed time step solution of the model equations. Solving model equations containing friction elements is a major challenge, since adaptive time step methods involving zero crossing detection are not feasible for real-time execution. This publication focuses on a technique for modeling complex drivetrain layouts that contain several friction elements like clutches and brakes. The main target of this contribution is to loosen requirements on maximum time step size which arise due to discontinuous friction modeling within the model equations. The proposed approach enables model-based calculations at larger time step sizes. This permits online calculation of complex gear transmission models at usual time rasters of common automotive control units.

Fixed time-step drivetrain observer for embedded automotive applications

This article proposes a technique for fixed timestep state observation of automotive gear transmissions containing multiple friction elements like clutches and brakes. As adaptive time-step methods are not feasible for embedded control, the solution of model equations containing friction elements is a major challenge. The suitability of the proposed approach for a complex gear transmission comprising multiple friction elements is demonstrated by modeling and fixed timestep simulation. Based on that model, a fixed time-step proportional integral state observer is derived, that permits embedded execution at execution rates of common automotive control units.

Survey on Control Schemes for Automated Driving on Highways

This survey focuses on trajectory tracking controllers of advanced driver assistance functions for comfortable and safe automated driving on highways. A short introduction to today’s driver assistance functions and their control objectives is given. Different control schemes that have been proposed during the past few years are discussed, including essentially PID control, fuzzy control, optimal state feedback controllers, sliding mode control, and model predictive control. The separation of longitudinal and lateral dynamics as well as their combination is tackled. In addition to the control design for assistance functions, this work lists prominent controllers of autonomous vehicle prototypes. A simulation of a highway scenario compares the performance of the different control approaches.

Energy Efficient Driving in Dynamic Environment: Considering Other Traffic Participants and Overtaking Possibility

This chapter studies energy efficient driving of (semi)autonomous electric vehicles operating in a dynamic environment with other traffic participants on a unidirectional, multi-lane road. This scenario is considered to be a so called hard problem, as constraints imposed are varying in time and space. Neglecting the constraints imposed from the surrounding traffic, the generation of an energy optimal speed trajectory may lead to bad results, with the risk of low driver acceptance when applied in a real driving environment. An existing approach satisfies constraints from surrounding traffic by modifying an existing unconstrained trajectory. In contrast to this, the proposed approach incorporates a leading vehicle’s motion as constraint in order to generate a new optimal speed trajectory in a global optimal sense. First simulation results show that energy optimal driving considering other vehicle participants is important. Even in simple setups significantly (8%) less energy is consumed at only 1.3% travelling time prolongation compared to the best constant speed driving strategy. Additionally, the proposed driving strategy is using 4.5% less energy and leads to 1.6% shorter travelling time compared to the existing overtaking approach. Using simulation studies, the proposed energy optimal driving strategy is analyzed in different scenarios.

Online calculation of diesel engine torque dynamics

In current vehicles the actual value of engine torque is provided as interface signal to powertrain control units. For transient operation the dynamic behaviour of the combustion engine has to be estimated e.g. in the transmission control unit in order to coordinate the powertrain components. Due to the lack of provided data on the dynamic behaviour it needs to be modelled separately in each control unit, mainly map-based with high calibration effort. The engine control unit (ECU) has access to the relevant sensor and reference values for online calculation of diesel engine dynamics. Within this publication a model-based online torque calculation is proposed taking into account information that is already available in standard ECUs. Additionally the current torque reserve is computed. The calculation of characteristic parameters defining the dynamic behaviour for torque requests is outlined. Based on these signals prediction of engine dynamics is simplified and can significantly reduce the calibration effort e.g. in transmission control unit. The presented paper describes the calculation method and compares simulation results to engine test bed measurements for validation.

Energy-Efficient Driving in Dynamic Environment: Globally Optimal MPC-like Motion Planning Framework

Predictive motion planning is a key for achieving energy-efficient driving, which is one of the major visions of automated driving nowadays. Motion planning is a challenging task, especially in the presence of other dynamic traffic participants. Two main issues have to be addressed. First, for globally optimal driving, the entire trip has to be considered at once. Second, the movement of other traffic participants is usually not known in advance. Both issues lead to increased computational effort. The length of the prediction horizon is usually large and the problem of unknown future movement of other traffic participants usually requires frequent replanning. This work proposes a novel motion planning approach for vehicles operating in dynamic environments. The above-mentioned problems are addressed by splitting the planning into a strategic planning part and situation-dependent replanning part. Strategic planning is done without considering other dynamic participants and is reused later in order to lower the computational effort during replanning phase.

Embedded Multi-core System for Design of Next Generation Powertrain Control Units

In recent days lots of effort is spent on the integration of multi-core processors also in embedded realtime systems domain for several reasons, such as continuously increasing performance requirements and stricter power limitations. This trend is reflected also in the automotive field. Another major aspect for this up-coming trend is the increasing amount of ECUs within the vehicle. Modern vehicles are equipped with 70 to 100 ECUs communicating trough the existing networks within the vehicle with each other to handle the necessary control SW system for vehicle operation. With upcoming multi-core technologies this amount could be reduced by combining different control application with possibly mixed criticality into one multi-core ECU.In this paper, a smart environment for the efficient validation of innovative system architectures based on multi-core platforms in order to be able to handle this future trend in the automotive field is presented. The motivation is to provide a hybrid environment (mixing simulation and physical components) for development of dependable automotive based on multicore controllers and thus reduce validation efforts and costs. The major objectives of the paper addresses the integration of multi-core technology in existing control applications in order to provide more computing resources for (a) improvement of existing functions and (b) development of novel functionalities and the electrical and functional integration of high dynamic controls with time based vehicle control algorithm.

A novel approach for model-based control of smooth and lossless gear shifts

In contrast to conventional and classical hybrid electric transmissions, multimode (hybrid electric) transmissions open new perspectives in gear shifting: The tradeoff between avoidance of propulsion torque interruption and dissipation in clutches can be resolved by smart utilization of the second, coequal, propulsion element, and rearrangement of standard shift phases (torque phase and inertia phase). The resulting smooth and lossless gear shifts reach a new level of performance combining comfort and efficiency. Therefore, modeling and control of these gear shifts is an ongoing automotive research topic since several years. However, so far there is no systematic, model-based approach, which would enable broad application in industry. This paper contributes to bridge this gap. The key point is a systematic determination of a consistent set of generalized coordinates, corresponding to a specific gear, i.e., set of locked clutches. This is achieved by exploiting the mechanical peculiarities of drivetrain topologies. Based on this, a straightforward transformation is proposed to derive a comprehensive state-space model for each gear of a given topology. This enables the statement of the control problem for smooth and lossless gear shifting in a novel compact and general form. Finally, a new shift procedure and a generic-model-based feedforward control is proposed and applied to an exemplary multimode transmission. Promising first simulation results confirm the significance of the proposed approach for further investigation and application.

Unifying Approach to Hybrid Control Software

The presented work focuses on a generic software architecture as a basis for complex hybrid control and energy management strategies for a very wide range of applications. A clear and transparent mode prioritization together with the requests generation form the fundamental structure within the proposed architecture which always ensures the secure handling of the complex system. Different application dependent hybrid features can easily be attached onto this core enabling calibration as well as testing in a straightforward manner due to their capsulation. The lean interfaces between core software and additional hybrid features are designed in a way to support software re-usability and scalability. Because of the very generic approach, derived control software can serve the entire spectrum from micro to full hybrid. The working principles of hybrid feature selection, request generation and mode transition are presented in detail for a selected example.

Virtual Concept Development on the Example of a Motorway Chauffeur

It is well known that the development of future automated driving faces big challenges regarding testing and validation. One strategy to tackle the drastically increased complex interaction of vehicle, driver, and environment is the so-called front-loading approach. This involves virtual development of new vehicle functions enabling early stage testing and validation. Within the funded project Technology Concepts for Advanced Highly Automated Driving (TECAHAD), this front-loading approach was applied for a concept development of an automated driving system (ADS)—the Motorway Chauffeur (MWC)—fully responsible for longitudinal and lateral motion of a car on motorways. In the following, we provide an insight on early stage virtual development of this ADS. Topics range from high-level requirements and functional safety investigations to software architecture and major components of the virtual implementation. Finally, first simulation results are shown for some MWC use cases, motivating the planned future real vehicle prototype implementation.