Computationally Efficient Approach for Preheating of Battery Electric Vehicles before Fast Charging in Cold Climates

This paper investigates battery preheating before fast charging, for a battery electric vehicle (BEV) driving in a cold climate. To prevent the battery from performance degradation at low temperatures, a thermal management (TM) system has been considered, including a high-voltage coolant heater (HVCH) for the battery and cabin compartment heating. Accordingly, an optimal control problem (OCP) has been formulated in the form of a nonlinear program (NLP), aiming at minimising the total energy consumption of the battery. The main focus here is to develop a computationally efficient approach, mimicking the optimal preheating behavior without a noticeable increase in the total energy consumption. The proposed algorithm is simple enough to be implemented in a low-level electronic control unit of the vehicle, by eliminating the need for solving the full NLP in the cost of only 1Wh increase in the total energy consumption

Optimal Thermal Management and Charging of Battery Electric Vehicles over Long Trips

This paper studies optimal thermal management and charging of a battery electric vehicle driving over long distance trips. The focus is on the potential benefits of including a heat pump in the thermal management system for waste heat recovery, and charging point planning, in a way to achieve optimality in time, energy, or their trade-off. An optimal control problem is formulated, in which the objective function includes the energy delivered by the charger(s), and the total charging time including the actual charging time and the detour time to and from the charging stop. To reduce the computational complexity, the formulated problem is then transformed into a hybrid dynamical system, where charging dynamics are modelled in the domain of normalized charging time. Driving dynamics can be modelled in either of the trip time or travel distance domains, as the vehicle speed is assumed to be known a priori, and the vehicle is only stopping at charging locations. Within the hybrid dynamical system, a binary variable is introduced for each charging location, in order to decide to use or skip a charger. This problem is solved numerically, and simulations are performed to evaluate the performance in terms of energy efficiency and time. The simulation results indicate that the time required for charging and total energy consumption are reduced up to 30.6% and 19.4%, respectively, by applying the proposed algorithm

Game engine based auralization of airborne sound insulation

Describing planned acoustic design by single number ratings yields a weak link to the subjective event, especially when the single number ratings are interpreted by others than experienced acousticians. When developing infrastructure, tools for decision making needs to address visual and aural perception. Visual perception can be addressed using game engines and this has enabled the establishment of tools for visualizations of planned constructions in virtual reality. Audio engines accounting for sound propagation in the game engine environment are steadily developing and have recently been made available. The aim of this project is to simulate airborne sound insulation by extending the support of recently developed audio engines directed towards virtual reality applications. The case studied was airborne sound insulation between two adjacent rooms in a building, the sound transmitted to the receiving room through the building structure resulting from sound pressure exciting the structural elements in the adjacent source room into vibration. The receiving room composed modelled space in the game engine Unreal Engine and Steam Audio was the considered audio engine. Sound transmission was modelled by filtering based on calculations of transmission loss via direct and flanking paths using the model included in the standard EN 12354-1. It was verified that the filtering technique for modelling sound transmission reproduced attenuations in correspondence with the predicted transmission loss. Methodology was established to quantify the quality of the audio engine room acoustics simulations. A room acoustics simulation was evaluated by comparing the reverberation time derived from simulation with theoretical predictions and the simulated reverberation time showed fair agreement with Eyring’s formula above its frequency threshold. The quality of the simulation of airborne sound insulation was evaluated relating the sound field in simulation to insulation classification by the standardized level difference. The spectrum of the simulated standardized level difference was compared with the corresponding sound transmission calculation for a modelled scenario. The simulated data displayed noticeable deviations from the transmission calculation, caused by the audio engine room acoustics simulation. However, the simulated data exhibited cancellation of favourable and unfavourable deviations from the transmission calculation resulting in a mean difference across the spectrum below the just noticeable difference of about 1 dB. Single number ratings was compared and the simulated single number rating was within the standard deviation of how the transmission model calculates predictions for a corresponding practical scenario measured in situ. Thus, the simulated data shows potential and comparisons between simulated data, established room acoustics simulation software and in situ measurements should further be made to deduce whether the deviations entails defects in the airborne sound insulation prediction or is an error imposed by the audio engine room acoustics simulation

Ohjelmistoyrityksen vaihtoehtojen arviointi kansainvälisen kumppanijakelukanavan käyttöönottoon

The primary international distribution channel for enterprise software vendors is to have partners deploy their software. This makes their operations more cost-effective and scalable because the partner is responsible for the more labour-intensive tasks of software deployment. In addition, partners with local offices have better contacts to potential customers. The goal of this thesis is to provide a framework and tools to support one vendor company's management in their decision-making when introducing the partner channel model. Its results are based mainly on interviews with the vendor's management and online form surveys conducted with the vendor's management and partner representatives. Two relevant partnership models were identified: system integrator and reseller. Of these, system integrator partners were considered more relevant due to the range of possibilities. Both models support the vendor's strategic goal of increasing the relative share of license revenue, which is usually more profitable than service revenue coming from, e.g., customization work. The objective of software distribution through partners was split into four sub-objectives and the best means for achieving these objectives were defined based on the results of the interviews and surveys. Attributes were then determined to make the objectives measurable and a partnering process was presented with different sub-objectives, which are relevant in different phases of the process. Although marketing and thought leadership measures were seen to make the potential partner interested in the vendor's software, existing reference customers were considered the best way to demonstrate product credibility. The best way to increase the value of the software for the partner is to provide well-defined methods to add value on top of the vendor's offering by customization and integration work. Integrating relevant parts of the vendor's organization with the partner's is necessary for successful project bids and deliveries. The vendor's management considered knowledge of the customer needs and experience from similar customers as the most important selection criteria for the partner.Kun pieni tai keskisuuri yritysasiakkaita palveleva ohjelmistoyritys hakee kasvua kansainvälisiltä markkinoilta, se rakentaa jakelukanavansa etsimällä kumppaneita, jotka toimittavat sen tuotetta kyseisillä markkinoilla. Tämä tekee ohjelmistoyrityksen toiminnasta kustannustehokkaampaa ja skaalautuvaa, kun kumppanin vastuulla ovat paljon miestyötunteja vaativat ohjelmistotoimituksen työtehtävät. Tämän lisäksi kumppanilla on paremmat suhteet paikallisiin asiakkaisiin. Työssä tarkastellaan ohjelmistoyritys Enoroa. Tavoitteena on muodostaa yritysjohdon päätöksentekoa tukevat kumppanijakelukanavan käyttöönottoon liittyvät tavoitteet, johdon preferenssit ja keinot tavoitteiden saavuttamisen mittaamiseen. Työssä tunnistettiin Enoron kannalta kaksi käypää kumppanimallia: systeemi-integraattori (SI) ja jälleenmyyjä. Ensimmäistä pidettiin tärkeämpänä, koska sen nähtiin tarjoavan enemmän kasvumahdollisuuksia. Molempien mallien nähtiin tukevan Enoron strategista tavoitetta lisätä yleensä hyvin kannattavien lisenssitulojen osuutta. Kumppanijakelukanavalle tunnistettiin neljä alatavoitetta, jotka linkitettiin prosessiin, jonka vaiheiden mukaan kumppanuus etenee. Parhaita keinoja tavoitteiden saavuttamiseen kartoitettiin haastatteluilla ja kyselylomakkeilla. Jotta kumppani kiinnostuisi Enoron tuotteesta, nykyistä asiakasportfoliota pidettiin parhaana keinona tuomaan tuotteelle uskottavuutta. Etenkin SI-kumppanit pitävät tärkeänä, että he voivat luoda Enoron tuotteen päälle lisää arvoa integroimalla tuote muihin järjestelmiin ja asiakaskohtaisilla räätälöinneillä. Tämän mahdollistaminen nähtiin parhaana keinona erottautua kilpailijoista, kun kumppani vertailee ohjelmistotoimittajia. Kouluttamisen lisäksi tiettyjen organisaation osien avaaminen kumppanille nähtiin välttämättömäksi, jotta yhteiset tarjoukset ja toimitukset olisivat onnistuneita. Enoron kannalta kumppanin tärkeimpiä ominaisuuksia olivat asiakastuntemus ja kokemus samankaltaisista asiakkaist

Game engine based auralization of airborne sound insulation

Describing planned acoustic design by single number ratings yields a weak link to the subjective event, especially when the single number ratings are interpreted by others than experienced acousticians. When developing infrastructure, tools for decision making needs to address visual and aural perception. Visual perception can be addressed using game engines and this has enabled the establishment of tools for visualizations of planned constructions in virtual reality. Audio engines accounting for sound propagation in the game engine environment are steadily developing and have recently been made available. The aim of this project is to simulate airborne sound insulation by extending the support of recently developed audio engines directed towards virtual reality applications. The case studied was airborne sound insulation between two adjacent rooms in a building, the sound transmitted to the receiving room through the building structure resulting from sound pressure exciting the structural elements in the adjacent source room into vibration. The receiving room composed modelled space in the game engine Unreal Engine and Steam Audio was the considered audio engine. Sound transmission was modelled by filtering based on calculations of transmission loss via direct and flanking paths using the model included in the standard EN 12354-1. It was verified that the filtering technique for modelling sound transmission reproduced attenuations in correspondence with the predicted transmission loss. Methodology was established to quantify the quality of the audio engine room acoustics simulations. A room acoustics simulation was evaluated by comparing the reverberation time derived from simulation with theoretical predictions and the simulated reverberation time showed fair agreement with Eyring’s formula above its frequency threshold. The quality of the simulation of airborne sound insulation was evaluated relating the sound field in simulation to insulation classification by the standardized level difference. The spectrum of the simulated standardized level difference was compared with the corresponding sound transmission calculation for a modelled scenario. The simulated data displayed noticeable deviations from the transmission calculation, caused by the audio engine room acoustics simulation. However, the simulated data exhibited cancellation of favourable and unfavourable deviations from the transmission calculation resulting in a mean difference across the spectrum below the just noticeable difference of about 1 dB. Single number ratings was compared and the simulated single number rating was within the standard deviation of how the transmission model calculates predictions for a corresponding practical scenario measured in situ. Thus, the simulated data shows potential and comparisons between simulated data, established room acoustics simulation software and in situ measurements should further be made to deduce whether the deviations entails defects in the airborne sound insulation prediction or is an error imposed by the audio engine room acoustics simulation

Artificial intelligence and Machine learning : a diabetic readmission study

The maturing of Artificial intelligence provides great opportunities for healthcare, but also comes with new challenges. For Artificial intelligence to be adequate a comprehensive analysis of the data is necessary along with testing the data in multiple algorithms to determine which algorithm is appropriate to use. In this study collection of data has been gathered that consists of patients who have either been readmitted or not readmitted to hospital within 30-days after being admitted. The data has then been analyzed and compared in different algorithms to determine the most appropriate algorithm to use

Optimal Thermal Management, Charging, and Eco-driving of Battery Electric Vehicles

This paper addresses optimal battery thermal management, charging, and eco-driving of a battery electric vehicle (BEV) with the goal of improving its grid-to-meter energy efficiency. Thus, an optimization problem is formulated, aiming at finding the optimal trade-off between trip time and charging cost. The formulated problem is then transformed into a hybrid dynamical system, where the dynamics in driving and charging modes are modeled with different functions and with different state and control vectors. Moreover, to improve computational efficiency, we propose modeling the driving dynamics in a spatial domain, where decisions are made along the traveled distance. Charging dynamics are modeled in a temporal domain, where decisions are made along a normalized charging time. The actual charging time is modeled as a scalar variable that is optimized simultaneously with the optimal state and control trajectories, for both charging and driving modes. The performance of the proposed algorithm is assessed over a road with a hilly terrain, where two charging possibilities are considered along the driving route and the battery is soaked to the ambient before departure. According to the results, trip time including driving and charging times, is reduced by 44%, compared to a case without active heating/cooling of the battery

Charge Planning and Thermal Management of Battery Electric Vehicles

This paper studies optimal thermal management and charging of a battery electric vehicle driving over long-distance trips. The focus is on the potential benefits of including a heat pump in the thermal management system for waste heat recovery, and charging point planning, in a way to achieve optimality in time, energy, or their trade-off. An optimal control problem is formulated, in which the objective function includes the energy delivered by the charger(s), and the total charging time including the actual charging time and the detour time to and from the charging stop. To reduce the computational complexity, the formulated problem is then transformed into a hybrid dynamical system, where charging dynamics are modeled in the domain of normalized charging time. Driving dynamics can be modeled in either trip time or travel distance domains, as the vehicle speed is assumed to be known a priori, and the vehicle is only stopping at charging locations. Within the hybrid dynamical system, a binary variable is introduced for each charging location, in order to decide whether to use or skip a charger. This problem is solved numerically, and simulations are performed to evaluate the performance in terms of energy efficiency and time. The simulation results indicate that the time required for charging and total energy consumption are reduced up to $30.6\%$ and $19.4\%$, respectively, by applying the proposed algorithm