A11
Electric Vehicles

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10:40
conference time (CEST, Berlin)
A Continuous Workflow With System Simulation and Integrated Reduced Order Modeling to Support the Design and Validation of EV Battery Thermal Management System
27/10/2021 10:40 conference time (CEST, Berlin)
Room: A
B. Honel, B. Lecointre (Siemens Digital Industries Software, FRA)
B. Honel, B. Lecointre (Siemens Digital Industries Software, FRA)
The critical element of a Battery Electric Vehicle (BEV) is certainly the battery system. It supplies the power to the motor while driving the vehicle range through its capacity but also represents the highest-cost component. Besides the cost, battery requirements lie on four main expectations, which are driving range, power, lifetime and safety. To combine them efficiently, a system level assessment needs to be performed in addition to a detailed focus on the battery pack itself. Thermal management is a key pillar of these four requirements. Keeping the battery cells temperature within a preset range, generally between 0 and 45°C, is mandatory to ensure optimal battery performance, lifetime and safety. In order to address efficiently this Battery Thermal Management challenge, we propose here to present a powerful step-by-step workflow based on System Simulation. This work describes how quickly a detailed battery model can be built with only a few available data thanks to dedicated and integrated productivity tools. While the resulting model enables to access temperature gradients within the battery pack, the final objective is to integrate it into a full vehicle model in order to assess behaviors on various configurations, this, during real-life critical transients such as fast-charging and RDEs scenarios. This lets endless possibilities for the optimization of the cooling pack design as well as the BTMS (Battery Thermal Management System) control strategies at early design stages. As you progress in the system design, simulation needs are also changing, especially when the control needs to be validated and tested in a Hardware-In-the-Loop (HIL) environment. We are hence proposing at the end of this work a continuity in the simulation framework by presenting how we seamlessly apply Reduced Order Model (ROM) techniques to this model in order to reduce simulation times, comply with fixed-step solver constraints, while preserving the essential behavior and dominant effects.
system simulation, ROM, Reduced Order Modeling, Battery, Battery Thermal Management, BTMS, control, HIL, Battery Electric Vehicle, BEV, battery pack, design, workflow, simulation
11:00
conference time (CEST, Berlin)
Approach on a Model Based Current Regulator Design for an Electric Drive Unit Using a Holistic System Design With Driver and Driving Cycle
27/10/2021 11:00 conference time (CEST, Berlin)
Room: A
H. Ott, M. Ruschitzka, R. Degen (Technische Hochschule Köln, DEU); M. Leijon (Uppsala University, DEU)
H. Ott, M. Ruschitzka, R. Degen (Technische Hochschule Köln, DEU); M. Leijon (Uppsala University, DEU)
Model based engineering is especially for the development of high performing control systems essentially. By means of suitable simplifications, they help to present technical relationships and express them mathematically. Thereby, active controllers to influence the system behavior could be developed in an efficient and reliable way. This paper deals with the design of a holistic simulation environment for an e-bike with a wheel hub motor in the rear wheel and a torque and speed sensor in the bottom bracket. A model-based approach to development using rapid control prototyping is chosen. The model design is chosen similar to the system design of the control system. The interfaces between the main models are also the interfaces of the later controller, which makes it easier to implement the system afterwards. The engine dynamics has been tested and adjusted on the model using a driving cycle. A special focus is on the interpretation of the drivers inputs by the bottom bracket sensor. At the interface between the sensor and the subordinate engine control system, any desired driving condition can be set for different types of drivers and driving situations by means of different characteristic curves. The scenarios investigated are derived from typical simulations needed during the development of e-bike drivetrains. They focus on the interaction of the hybrid system consisting of human driver and engine torque. Especially the synchronization of torques and the reaction to fast increasing stimuli were investigated. The results show a valid performance of the developed algorithm. The e-motor torque oscillates quickly and the synchronization works fine. Additionally, the algorithm to smooth the pedaling fluctuations and thereby the torque fluctuations work quite well, whereby a smooth torque is implemented. Next steps are the integration of supporting modes and the demand-orientated control.
Electric drive unit, model based engineering, multibody simulation, control system
11:20
conference time (CEST, Berlin)
Electric Vehicle Simulation Platform: One Model to Rule Them All
27/10/2021 11:20 conference time (CEST, Berlin)
Room: A
R. Nicolas, L. Broglia (Siemens Digital Industries Software, FRA)
R. Nicolas, L. Broglia (Siemens Digital Industries Software, FRA)
Electric vehicles are booming. There are plenty of engineering programs that are initiated each year. Engineering an electric vehicle requires advanced methods and tools. But it happens that these tools can barely exchange data between each others. Hence, understanding systems' interactions and boundary conditions can be complicated. It is however important to connect different engineering fields, different components and systems engineers, different domain specialist, to limit issues and errors happening at the interfaces. Creating, managing and maintaining a digital thread is a good way to safeguard what is happening at these interfaces and avoid communication issues. This paper showcases how a single system simulation model can be used to gather data coming from different components engineers and simulation engineers in order to master the integration of these components. The import of data can be done through the use of FMUs (Functional Mock-up Units) or the use of Apps. Battery data are imported from Battery cell design simulation tool, Inverter power electronics model is imported from an EDA (Electronic Design Automation) tool, inverter thermal model is imported from a CFD code and the electric machine model is imported from an electromagnetic simulation tool. The purpose of this simulation platform is to be able to perform a high level synthesis of the vehicle performances. Attributes like range, longitudinal performance and thermal safety are assessed. In the paper, we will go through the comparison between two inverter semi-conductors technologies (IGBT and SiC MOSFET) and two cooling systems for the inverter itself (direct water cooling or indirect water cooling). The pros and cons of the different technologies are discussed as well as the process to setup the model and to gather all the data. Some perspectives regarding more use cases that could be done with the platform will also be introduced like Hardware-In-the-Loop software verification or Predictive maintenance/fleet monitoring.
System simulation, integration, reduced order model, inverter,
11:40
conference time (CEST, Berlin)
The Story Behind Building the World’s Fastest Fully Electric Aircraft
27/10/2021 11:40 conference time (CEST, Berlin)
Room: A
S. Hafid (Ansys Europe Ltd., GBR)
S. Hafid (Ansys Europe Ltd., GBR)
Electrification is a major initiative across the aviation sector. Rolls-Royce is leading a small team of companies, including Electroflight (Gloucester), aspiring to break the record for the world’s fastest (300+ mph) full electric aircraft: project ACCEL (Accelerating the Electrification of Flight). To succeed, the ACCEL project must deliver ground-breaking new technology across electrical systems, energy storage, systems integration and controls. The battery assembly for ACCEL is the largest, most energy dense assembly ever used to an aviation application. A crucial aspect of the project success is managing battery thermal performance, throughout the aircraft operation. The batteries are assembled from individual, high performance cells, into multiple sub-assemblies and strings, each with active cooling systems. The cooling system comprises a series of heat-exchanger plates, feed by cooling water, through a series of inlet and outlet manifolds. The design of the inlet and outlet manifolds, in both forward and reverse flow, with a limited space envelope, an even flow split and with minimum pressure loss, is essential for the cooling system performance. In addition, the project, as a whole, is running to very tight timescales, so a fast turnaround at all stages is essential. Electroflight partnered with ANSYS to assist in the optimisation of the cooling system, specifically the cooling manifolds design. Within the overall project constraints, this required a new engineering design approach. A two-stage interactive and smart optimisation workflow was used for this study: • Firstly, an interactive GPU accelerated physics solver was used to explore the fluid volume shape, to optimise the manifold design and flow splits. This technique allowed manipulation of geometry, fluid types and physical inputs, with instantaneous feedback on changes in system performance. • A second stage using traditional CFD, with conventional meshing and discretisation, was used to validate the predicted manifolds performance and an Adjoint optimisation was performed, to tune the design and minimize the pressure drops. The adjoint solver calculates the best-performing shape with respect to a target variable(s) and automatically morphs the fluid volume shape. The results of the adjoint optimization can then be exported and reverse engineered, for manufacture. This workflow established optimal manifold concepts, that would achieve an even flow split, with the Adjoint optimisation further reducing the pressure drop by up to 46%. Subsequent adjustments to the manifold arrangement, required due to changes in the feed pipes and adjustments to the space envelope, were easily addressed by revisiting the workflow process. This project has demonstrated that a combined approach of fast-interactive physics simulation and adjoint optimisation, can rapidly derive an optimal solution, replacing the need for otherwise lengthy parametric study.
Electrification, Designer-oriented simulation, battery, cooling system, rapid optimization
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