29 September - 1 October, 2020
| Berlin, Germany
Agenda Day 2
8:30 am - 9:00 am
Registration and welcome coffee
9:00 am - 9:10 am
Opening remarks by conference chairman
Bo Johansson -
Director Strategy & Special Projects,
Volvo Group, Sweden
9:10 am - 9:50 am
Panel discussion | BMS and control software
Bo Johansson -
Director Strategy & Special Projects,
Volvo Group, Sweden
Faisal Altaf - Principal Research Engineer & Project Manager AE and Research—ESS Control & SW, Volvo Group Trucks Technology
Hans Harjung - CEO & Founder, e-moove GmbH
In order to have an efficient BMS, there is the need to ensure that the we can optimize the functionality of the battery. This interactive panel discussion will focus on two main important topics:
1 | The role of (new) control algorithms and the benefits from methodology to extend lifetime
After the first discussion the panel will focus on:
2 | BMS for autonomous driving: What are the challenges and opportunities
Faisal Altaf
Principal Research Engineer & Project Manager AE and Research—ESS Control & SWVolvo Group Trucks Technology
9:50 am - 10:30 am
Design BMS software architecture for performance, safety, modifiability, testability
Junghwan Lee -
Principle engineer BMS,
SVOLT
Software architecture directly affects quality, cost, development schedule, which is required to cover both functional requirements and quality attributes. However, handling quality attributes makes difference in architecture
• Identifying fragile BMS SW components against system requirement changes or project variation.
• Meeting safety requirements in architecture with consideration of performance
• Design consideration in Dual core architecture
10:30 am - 11:00 am
Refreshment break and networking
11:00 am - 11:40 am
A review of state of health estimation methods of batteries in electric buses to adapt in BMS
Agnieszka Domeracka -
Junior Design Engineer, Research and Development Department,
Solaris Bus & Coach
The main issues of battery management system in automotive applications, especially for electric buses are safety and lifetime. According to this plenty of state of health estimating methods are developed nowadays. However the key issue is to find method which will ensure accuracy and computational complexity will be not too large to adapt in BMS. The review from an electric buses producer will be presented:
• Classification of SOH estimation methods: experimental techniques and adaptive models
• Indicating the battery parameters which affect on battery degradation
• Review of SOH estimation methods for batteries in electric buses
• How to describe ageing mechanisms using mathematical equations?
Agnieszka Domeracka
Junior Design Engineer, Research and Development DepartmentSolaris Bus & Coach
11:40 am - 12:20 pm
Adaptive battery control
Torsten Wik -
Professor, Electrical engineering,
Chalmers University of Technology
• How to make algorithms cope with changes in operating conditions and battery health
while maximizing performance
• Use of traditional equivalent circuit modelling
• Base our algorithms on limitations on internal physical variables instead of terminal voltage
and external temperature
12:20 pm - 1:00 pm
Li-ion battery / Supercapacitor energy storage system
Théophile Paul -
R&D electrical engineer - PhD student,
ICube Laboratory INSA
The massive diffusion of electric vehicles can only be achieved if the energy performance and driving comfort remain equivalent to traditional combustion vehicles. Nowadays, Li-ion battery single sources used in the automotive sector are too limited compared to the energy density of fossil fuels. One of the ideas to overcome this problem is to use a Li-ion battery / Supercapacitor hybrid energy storage system.
1:00 pm - 2:00 pm
Networking Luncheon
2:00 pm - 2:30 pm
The Influence of Degradation Path Dependency on State of Health Models for Lithium Ion Batteries in Electric Vehicles
Trishna Raj -
PhD candidate,
University of Oxford
Battery ageing for EVs where reliability of the vehicle is dependent on battery performance, capacity and lifetime- Understanding path dependency and the importance of incorporating path dependency in EV lifetime/performance models- Data collected from experiemental campaign to prove the impact of path dependent degradation on cell performance
2:30 pm - 3:10 pm
Data-based fault detection – Detachment of a parallel-connected cell
Alexander Fill -
Ph.D. Student, Research and Development,
Daimler AG
In order to meet the power and energy requirements of large-scale applications such as electric vehicles, lithium-ion cells are usually connected in parallel. This connection enables a closed circuit even if one or more cells within the parallel configuration are disconnected. This type of connection fault can lead to electrical and thermal overload of the remaining former parallel-connected cells. A data-based algorithm is shown which detects and localizes this connection error via voltage measurements. The algorithm is validated by measurements on a module of three serial-connected cells, each consisting of two parallel-connected 50 Ah pouch cells. Under typical driving loads an interruption is detected in less than 20 seconds.
3:10 pm - 3:50 pm
Importance of Energy storage systems
Carlos Silva -
Software Developer,
Daimler AG
• Current requirements and expectations
• How to overcome the challenges
• Future roadmap in the automotive world
3:50 pm - 4:20 pm
Refreshment break, networking and end of the conference
4:20 pm - 5:20 pm
Round table session | Mix and Discuss EV High Power Charging and Battery
Management Systems and What are the requirements for future Battery Management Systems?
In these closing twin-sessions, we invite delegates to mix & discuss by choosing 2 out of 6 deep dive topics, and elaborate each with experts from the two conferences. For each topic you chose, you have 30 minutes to discuss it in your group. The results will be presented at the end.
16:20 Session I • 16:50 Break for Switching • 16:55 Session II
TABLE A | Defining battery ageing model adapted to vehicle real usage
Philippe Gyan, Battery Innovations Research Engineer, Renault
TABLE B | Energy storages systems in EV/HEVs Energy storage systems and their current status
and challenges
Théophile Paul, R&D electrical engineer - PhD student, ICube Laboratory INSA
TABLE C | Design DCU (Domain Control Unit) with BMS
• Which functions to swift from BCU to DCU / cloud? (f.e. advanced SOH calc., more calc. resources available: DCU)
• Which functions will remain to BCU and why (f.e. safety functions, relays driving, isolation measurement, HW interfacing
Chrysanthos Tzivanopoulos, Senior engineer of the Battery Management System Hardware
Development for Lithium Ion Batteries, Robert Bosch GmbH
TABLE D | Battery cell solutions to enable high power charging Electrolytes, electrodes and internal resistance – solutions to overcome the limits
Dr. Stefan Permien, CEO, UniverCell Holding GmbH
TABLE E – Vehicle to vehicle charging – what are the possible configurations? Direct DC to DC, or through a station?
Rob Jerger, Technical Specialist - Charge Control Systems, Jaguar LandRover
