5.2 Smart Energy and Automotive Systems

Time	Label	Presentation Title Authors
08:30	5.2.1	SOH-AWARE ACTIVE CELL BALANCING STRATEGY FOR HIGH POWER BATTERY PACKS Speaker: Alma Proebstl, Technical University of Munich, DE Authors: Alma Proebstl¹, Sangyoung Park¹, Swaminathan Narayanaswamy², Sebastian Steinhorst¹ and Samarjit Chakraborty¹ ¹Technical University of Munich, DE; ²TUM CREATE, SG Abstract Short drive range due to limited battery capacity and high battery depreciation costs persist to be the main deterrents to the wide adoption of Electric Vehicles (EVs). High power battery packs consisting of a large number of battery cells require extensive management, such as State of Charge (SOC) balancing and thermal management, in order to keep the operating conditions within a safe range. In this paper, we propose a novel State of Health (SOH)-aware active cell balancing technique, which is capable of extending the cycle life of the whole battery pack. In contrast to the state-of-the-art active cell balancing techniques, the proposed technique allows cells to have different SOC values such that aging is mitigated when an EV trip does not require the full capacity. Based on the observation that preferring cells with higher SOH over cells with lower SOH extends cycle life, the technique identifies the charge transfers between cells that would benefit the most. We find that with our proposed scheme, aging could be mitigated by up to 23.5% over passive cell balancing and 17.6% over active SOC cell balancing. Download Paper (PDF; Only available from the DATE venue WiFi)
09:00	5.2.2	(Best Paper Award Candidate) GIS-BASED OPTIMAL PHOTOVOLTAIC PANEL FLOORPLANNING FOR RESIDENTIAL INSTALLATIONS Speaker: Sara Vinco, Politecnico di Torino, IT Authors: Sara Vinco, Lorenzo Bottaccioli, Edoardo Patti, Andrea Acquaviva, Enrico Macii and Massimo Poncino, Politecnico di Torino, IT Abstract Shading is a crucial issue for the placement of PV installations, as it heavily impacts power production and the corresponding return of investment. Nonetheless, residential rooftop installations still rely on rule-of-thumb criteria and on gross estimates of the shading patterns, while more optimized approaches focus solely on the identification of suitable surfaces (e.g., roofs) in a larger geographic area (e.g., city or district). This work addresses the challenge of identifying an optimal (with respect to the overall energy production) placement of PV panels on a roof. The novel aspect of the proposed solution lies in the possibility of having a sparse, irregular placement of individual modules so as to better exploit the variance of solar data. The latter are represented in terms of the distribution of irradiance and temperature values over the roof, as elaborated from historical traces and Geographical Information System (GIS) data. Experimental results will prove the effectiveness of the algorithm through three real world case studies, and that the generated optimal solutions allow to increase power production by up to 28% with respect to rule-of-thumb solutions. Download Paper (PDF; Only available from the DATE venue WiFi)
09:30	5.2.3	CELL-BASED UPDATE ALGORITHM FOR OCCUPANCY GRID MAPS AND HYBRID MAP FOR ADAS ON EMBEDDED GPUS Speaker: Jörg Fickenscher, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), DE Authors: Jörg Fickenscher¹, Jens Schlumberger¹, Frank Hannig¹, Mohamed Essayed Bouzouraa² and Jürgen Teich¹ ¹Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), DE; ²Concept Development Automated Driving, AUDI AG, DE Abstract Advanced Driver Assistance Systems (ADASs), such as autonomous driving, require the continuous computation and update of detailed environment maps. Today's standard processors in automotive Electronic Control Units (ECUs) struggle to provide enough computing power for those tasks. Here, new architectures, like Graphics Processing Units (GPUs) might be a promising accelerator candidate for ECUs. Current algorithms have to be adapted to these new architectures when possible, or new algorithms have to be designed to take advantage of these architectures. In this paper, we propose a novel parallel update algorithm, called cell-based update algorithm for occupancy grid maps, which exploits the highly parallel architecture of GPUs and overcomes the shortcomings of previous implementations based on the Bresenham algorithm on such architectures. A second contribution is a new hybrid map, which takes the advantages of the classic occupancy grid map and reduces the computational effort of those. All algorithms are parallelized and implemented on a discrete GPU as well as on an embedded GPU (Nvidia Tegra K1 Jetson board). Compared with the stateof- the-art Bresenham algorithm as used in the case of occupancy grid maps, our parallelized cell-based update algorithm and our proposed hybrid map approach achieve speedups of up to 2.5 and 4.5, respectively. Download Paper (PDF; Only available from the DATE venue WiFi)
10:00	IP2-5, 203	IMPROVING FAST CHARGING EFFICIENCY OF RECONFIGURABLE BATTERY PACKS Speaker: Alexander Lamprecht, TUM CREATE, SG Authors: Alexander Lamprecht¹, Swaminathan Narayanaswamy¹ and Sebastian Steinhorst² ¹TUM CREATE, SG; ²Technical University of Munich, DE Abstract Recently, reconfigurable battery packs that can dynamically modify the electrical connection topology of their individual cells are gaining importance. While several circuit architectures and management algorithms are proposed in the literature, the electrical characteristics of the reconfiguration circuit architectures are not sufficiently studied so far. In this paper, we derive a detailed analytical model for a state-of-the-art reconfiguration architecture capturing the losses introduced by the parasitic resistances of the circuit components. For the first time, we propose a novel fast charging strategy using the reconfiguration architecture that significantly reduces the power losses in comparison to conventional battery packs. Moreover, using the analytical model, we highlight the challenges faced by existing reconfiguration architectures using state-of-the-art components and we derive the specifications for the switches which are essential for improving the energy efficiency of such reconfigurable battery packs. Download Paper (PDF; Only available from the DATE venue WiFi)
10:01	IP2-6, 816	CLOUD-ASSISTED CONTROL OF GROUND VEHICLES USING ADAPTIVE COMPUTATION OFFLOADING TECHNIQUES Speaker: Soheil Samii, General Motors R&D, Warren, MI 48090, US Authors: Arun Adiththan¹, Ramesh S² and Soheil Samii² ¹City University of New York, US; ²General Motors R&D, US Abstract The existing approaches to design efficient safety-critical control applications is constrained by limited in-vehicle sensing and computational capabilities. In the context of automated driving, we argue that there is a need to leverage resources "out-of-the-vehicle" to meet the sensing and powerful processing requirements of sophisticated algorithms (e.g., deep neural networks). To realize the need, a suitable computation offloading technique that meets the vehicle safety and stability requirements, even in the presence of unreliable communication network, has to be identified. In this work, we propose an adaptive offloading technique for control computations into the cloud. The proposed approach considers both current network conditions and control application requirements to determine the feasibility of leveraging remote computation and storage resources. As a case study, we describe a cloud-based path following controller application that leverages crowdsensed data for path planning. Download Paper (PDF; Only available from the DATE venue WiFi)
10:00		End of session Coffee Break in Exhibition Area Coffee Breaks in the Exhibition Area On all conference days (Tuesday to Thursday), coffee and tea will be served during the coffee breaks at the below-mentioned times in the exhibition area (Terrace Level of the ICCD). Lunch Breaks (Großer Saal + Saal 1) On all conference days (Tuesday to Thursday), a seated lunch (lunch buffet) will be offered in the rooms "Großer Saal" and "Saal 1" (Saal Level of the ICCD) to fully registered conference delegates only. There will be badge control at the entrance to the lunch break area. Tuesday, March 20, 2018 Coffee Break 10:30 - 11:30 Lunch Break 13:00 - 14:30 Awards Presentation and Keynote Lecture in "Saal 2" 13:50 - 14:20 Coffee Break 16:00 - 17:00 Wednesday, March 21, 2018 Coffee Break 10:00 - 11:00 Lunch Break 12:30 - 14:30 Awards Presentation and Keynote Lecture in "Saal 2" 13:30 - 14:20 Coffee Break 16:00 - 17:00 Thursday, March 22, 2018 Coffee Break 10:00 - 11:00 Lunch Break 12:30 - 14:00 Keynote Lecture in "Saal 2" 13:20 - 13:50 Coffee Break 15:30 - 16:00

Time

Label

Presentation Title
Authors

08:30

5.2.1

SOH-AWARE ACTIVE CELL BALANCING STRATEGY FOR HIGH POWER BATTERY PACKS
Speaker:
Alma Proebstl, Technical University of Munich, DE
Authors:
Alma Proebstl¹, Sangyoung Park¹, Swaminathan Narayanaswamy², Sebastian Steinhorst¹ and Samarjit Chakraborty¹
¹Technical University of Munich, DE; ²TUM CREATE, SG
Abstract
Short drive range due to limited battery capacity and high battery depreciation costs persist to be the main deterrents to the wide adoption of Electric Vehicles (EVs). High power battery packs consisting of a large number of battery cells require extensive management, such as State of Charge (SOC) balancing and thermal management, in order to keep the operating conditions within a safe range. In this paper, we propose a novel State of Health (SOH)-aware active cell balancing technique, which is capable of extending the cycle life of the whole battery pack. In contrast to the state-of-the-art active cell balancing techniques, the proposed technique allows cells to have different SOC values such that aging is mitigated when an EV trip does not require the full capacity. Based on the observation that preferring cells with higher SOH over cells with lower SOH extends cycle life, the technique identifies the charge transfers between cells that would benefit the most. We find that with our proposed scheme, aging could be mitigated by up to 23.5% over passive cell balancing and 17.6% over active SOC cell balancing.
Download Paper (PDF; Only available from the DATE venue WiFi)

09:00

5.2.2

(Best Paper Award Candidate)
GIS-BASED OPTIMAL PHOTOVOLTAIC PANEL FLOORPLANNING FOR RESIDENTIAL INSTALLATIONS
Speaker:
Sara Vinco, Politecnico di Torino, IT
Authors:
Sara Vinco, Lorenzo Bottaccioli, Edoardo Patti, Andrea Acquaviva, Enrico Macii and Massimo Poncino, Politecnico di Torino, IT
Abstract
Shading is a crucial issue for the placement of PV installations, as it heavily impacts power production and the corresponding return of investment. Nonetheless, residential rooftop installations still rely on rule-of-thumb criteria and on gross estimates of the shading patterns, while more optimized approaches focus solely on the identification of suitable surfaces (e.g., roofs) in a larger geographic area (e.g., city or district). This work addresses the challenge of identifying an optimal (with respect to the overall energy production) placement of PV panels on a roof. The novel aspect of the proposed solution lies in the possibility of having a sparse, irregular placement of individual modules so as to better exploit the variance of solar data. The latter are represented in terms of the distribution of irradiance and temperature values over the roof, as elaborated from historical traces and Geographical Information System (GIS) data. Experimental results will prove the effectiveness of the algorithm through three real world case studies, and that the generated optimal solutions allow to increase power production by up to 28% with respect to rule-of-thumb solutions.
Download Paper (PDF; Only available from the DATE venue WiFi)

09:30

5.2.3

CELL-BASED UPDATE ALGORITHM FOR OCCUPANCY GRID MAPS AND HYBRID MAP FOR ADAS ON EMBEDDED GPUS
Speaker:
Jörg Fickenscher, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), DE
Authors:
Jörg Fickenscher¹, Jens Schlumberger¹, Frank Hannig¹, Mohamed Essayed Bouzouraa² and Jürgen Teich¹
¹Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), DE; ²Concept Development Automated Driving, AUDI AG, DE
Abstract
Advanced Driver Assistance Systems (ADASs), such as autonomous driving, require the continuous computation and update of detailed environment maps. Today's standard processors in automotive Electronic Control Units (ECUs) struggle to provide enough computing power for those tasks. Here, new architectures, like Graphics Processing Units (GPUs) might be a promising accelerator candidate for ECUs. Current algorithms have to be adapted to these new architectures when possible, or new algorithms have to be designed to take advantage of these architectures. In this paper, we propose a novel parallel update algorithm, called cell-based update algorithm for occupancy grid maps, which exploits the highly parallel architecture of GPUs and overcomes the shortcomings of previous implementations based on the Bresenham algorithm on such architectures. A second contribution is a new hybrid map, which takes the advantages of the classic occupancy grid map and reduces the computational effort of those. All algorithms are parallelized and implemented on a discrete GPU as well as on an embedded GPU (Nvidia Tegra K1 Jetson board). Compared with the stateof- the-art Bresenham algorithm as used in the case of occupancy grid maps, our parallelized cell-based update algorithm and our proposed hybrid map approach achieve speedups of up to 2.5 and 4.5, respectively.
Download Paper (PDF; Only available from the DATE venue WiFi)

10:00

IP2-5, 203

IMPROVING FAST CHARGING EFFICIENCY OF RECONFIGURABLE BATTERY PACKS
Speaker:
Alexander Lamprecht, TUM CREATE, SG
Authors:
Alexander Lamprecht¹, Swaminathan Narayanaswamy¹ and Sebastian Steinhorst²
¹TUM CREATE, SG; ²Technical University of Munich, DE
Abstract
Recently, reconfigurable battery packs that can dynamically modify the electrical connection topology of their individual cells are gaining importance. While several circuit architectures and management algorithms are proposed in the literature, the electrical characteristics of the reconfiguration circuit architectures are not sufficiently studied so far. In this paper, we derive a detailed analytical model for a state-of-the-art reconfiguration architecture capturing the losses introduced by the parasitic resistances of the circuit components. For the first time, we propose a novel fast charging strategy using the reconfiguration architecture that significantly reduces the power losses in comparison to conventional battery packs. Moreover, using the analytical model, we highlight the challenges faced by existing reconfiguration architectures using state-of-the-art components and we derive the specifications for the switches which are essential for improving the energy efficiency of such reconfigurable battery packs.
Download Paper (PDF; Only available from the DATE venue WiFi)

10:01

IP2-6, 816

CLOUD-ASSISTED CONTROL OF GROUND VEHICLES USING ADAPTIVE COMPUTATION OFFLOADING TECHNIQUES
Speaker:
Soheil Samii, General Motors R&D, Warren, MI 48090, US
Authors:
Arun Adiththan¹, Ramesh S² and Soheil Samii²
¹City University of New York, US; ²General Motors R&D, US
Abstract
The existing approaches to design efficient safety-critical control applications is constrained by limited in-vehicle sensing and computational capabilities. In the context of automated driving, we argue that there is a need to leverage resources "out-of-the-vehicle" to meet the sensing and powerful processing requirements of sophisticated algorithms (e.g., deep neural networks). To realize the need, a suitable computation offloading technique that meets the vehicle safety and stability requirements, even in the presence of unreliable communication network, has to be identified. In this work, we propose an adaptive offloading technique for control computations into the cloud. The proposed approach considers both current network conditions and control application requirements to determine the feasibility of leveraging remote computation and storage resources. As a case study, we describe a cloud-based path following controller application that leverages crowdsensed data for path planning.
Download Paper (PDF; Only available from the DATE venue WiFi)

10:00

End of session
Coffee Break in Exhibition Area

Coffee Breaks in the Exhibition Area

On all conference days (Tuesday to Thursday), coffee and tea will be served during the coffee breaks at the below-mentioned times in the exhibition area (Terrace Level of the ICCD).

Lunch Breaks (Großer Saal + Saal 1)

On all conference days (Tuesday to Thursday), a seated lunch (lunch buffet) will be offered in the rooms "Großer Saal" and "Saal 1" (Saal Level of the ICCD) to fully registered conference delegates only. There will be badge control at the entrance to the lunch break area.

Tuesday, March 20, 2018