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LIB Technology Symposium
Large Lithium Ion Battery Technology & Application (LLIBTA)
Monday, June 15 to Wednesday, June 17, 2015
Engineering Track

Advanced Automotive Battery Conferences

AABC 2015 – LIB Technology Symposium - Engineering Track


Session 3B:

Battery Pack Electrical Design

Considering the high-voltage, long life, and high-reliability requirements of the automotive and stationary applications on the one hand, and the volatility of the Li-Ion chemistry on the other, current battery packs include multiple electrical and mechanical components to ensure system reliability. In this session, pack designers and electrical/electronic component suppliers will discuss the new developments that aim to simplify system design and reduce cost while ensuring system reliability.



Uwe Wiedemann
Session Chairman:
Uwe Wiedemann, Senior Product Manager, AVL List GmbH


Uwe Wiedemann studied Mechatronics at the University of Aalen, Germany and the University of Teesside, GB. He received a PhD degree from the University of Ulm for the investigation of NiMH ageing mechanism in HEVs. From 2003 onwards he was involved in battery management system software development and other development tasks around electrochemical energy storage systems. After working in research and development departments at Daimler AG and Robert Bosch GmbH, he joined AVL List’s Global Battery Competence Team in 2009. His current position is Senior Product Manager.

  1. Complexity of Electrics in a Battery – an Overview of Components and Their Challenges
    Uwe Wiedemann, Senior Product Manager, AVL List GmbH
    Current battery systems in electric vehicles often show weaknesses in reliability that cannot always be traced back to the cell technology or cell chemistry. One of the main contributors are the electric circuit and the electric components. During battery pack development, there are several different requirements which has to be fulfilled from each component. Additional to function, there are also specifications concerning safety, weight, cost, reliability and misuse.
    The presentation will explain an appropriate method, using MBSE (model-based system engineering), to reduce the risk of failure and to point out the key parameters during development.
    Furthermore, the particular challenges for each component will be identified which needs to be considered during development phase and also how they will be handled.

    The focus will be on following components:

    • Relay
    • Fuse
    • Precharge circuit
    • Current Sensor
    • Cell / Module connector.
    Our activities are focusing to find a proper way to fulfill all requirements, to optimize the battery system and to prevent an early drop out caused by an avoidable mistake during development.
  2. Battery Management Systems’ (BMS) Impact on Battery Safety and Cost
    Kevin Konecky, Total Battery Consulting
    Lithium-Ion battery systems are an enabling technology in the propagation of xEV’s (Hybrid-Electric Vehicles, Plug-in Hybrid-Electric Vehicles and Electric Vehicles). Two important aspects of the battery system are safety and cost. As xEV’s are becoming more regularly accepted by the automotive consumer, market growth will be hindered by high costs and/or safety issues. The Battery Management System (BMS) is one of the key subsystems of the battery system that can have a large impact on these two key areas.

    The first point of this discussion will talk about the various architectures of BMS and their cost impact on the battery system along with associated tradeoffs.

    The second point will discuss the safety aspects of the BMS; including issues that can be introduced by improper BMS development as well as how robust BMS development can enhance battery system safety.

  3. Top 5 Challenges with BMS Testing
    Peter Blume, President and Founder, Bloomy
    How do you comprehensively test ALL of the battery management system functions? How do you test the BMS without using hazardous battery packs? How do you test the BMS response to overvoltage, over temperature, or other dangerous conditions without jeopardizing the safety of people and assets? How do you test embedded control algorithms such as cell balancing, SOC, and SOH in real time? How do you test the BMS while the cells it controls are under development or not available? In this presentation, Peter Blume presents how battery simulation and HIL testing, using commercially available technology, is the safe and efficient means of solving the top five BMS test challenges.

    Featured products:

    • The Battery Simulator 1200 is a 12-cell simulator that is the building block of all of Bloomy’s BMS test products. Each cell is individually programmable to sink and source current at 0-5VDC. It is analogous to a small substack, except it is not susceptible to the hazards of real batteries. Since it is isolated to 1,000 Volts, you can combine multiple 12-cell simulators in series in order to simulate a larger pack.
    • The BMS HIL Test System is used to simulate a complete battery pack in order to test the BMS in real time. It is ideal for iteratively testing and optimizing BMS firmware, including cell balancing algorithms, safety interlocks, response to over temperature, and many more conditions. Multiple Battery Simulator 1200 units are connected in series in order to simulate a larger pack. The software runs a set of Simulink or other models to simulate the specific battery chemistry, drive profiles, charge/discharge cycles, thermal runaway, and various faults.
  4. Wireless Battery Management Systems
    Andrew Chon, Founder and CEO, Navitas Solutions
    In previous AABCs, Navitas Solutions Inc. has presented an innovative wireless battery management system (WBMS™). The WBMS™ architecture adopts wireless communication technologies between a master BMS and battery cell sensors. Without the sensing wire-harness, the WBMS™ can address many challenging issues of the conventional wire-based approaches. For example, battery pack design can be drastically simplified and pack manufacturing process can be greatly automated. Battery cell voltage can be measured simultaneously by broadcasting the commands. No isolators are required because the high voltage area is physically separated by the wireless channel. Consequently, the number of components can be significantly reduced, resulting in fewer failure points for low-cost, robust, and reliable battery packs.

    Navitas Solutions Inc. also has presented various test results of the WBMS™ chipset to demonstrate the feasibility of the chipset for automotive applications. The test results include performance tests such as sensor measurements accuracy, the reliability of wireless communication, environmental tests under harsh operating conditions, and the EMC tests. The results proved that the WBMS™ chipset is reliable and robust enough to be used for automotive applications.

    In this paper, we will present the next generation WBMS™ architecture that enables three major improvements: (1) further BMS cost reduction, (2) more secure data communication, and (3) drastically flexibility in BMS pack configuration. We will also present video demonstration of the operation during the presentation. The new WBMS™ chipset solution will facilitate a battery pack that is simplified, light-weight, reliable, robust, and most importantly, inexpensive.

  5. Implementing Real Time Model-Based Control in a BMS
    John Milios, Chief Executive Officer, Sendyne
    Complex control applications, such as Battery Management Systems, benefit greatly from the use of model-based control techniques.  The method today for embedded models works like this: a model, typically described as a set of differential algebraic equations (DAEs), is developed and tested in Computer Aided Engineering environment (CAE). Custom code is then generated for the embedded environment. This code does not contain useful features of the CAE environment and model changes require a high-cost repetition of the process. In this presentation we discuss the advantages of using Sendyne's RTSim™, a high speed model solver for real-time embedded control applications. RTSim™ takes, as input, a model’s differential algebraic equations (DAEs) and solves them directly on an embedded processor, eliminating the need for custom programming.  RTSim™ provides all the features of a State-of-the-Art solver, such as automatic differentiation, sensitivities computed analytically on-the-fly, sparse matrix techniques, and variable time step – yet occupies less than 300 kB of memory. This coupled with a high execution speed makes it possible to utilize realistic, physics-based models for battery system control and monitoring.
    We will discuss:
    • Overview of model based control
    • How models are embedded today and limitations to this method
    • Model Reference Adaptive Control (MRAC)
    • The RTSim paradigm and how it compares to custom code
    • Performance of RTSim in battery modelling