Battery management system for electric racing cars

With the introduction of the electrics cars into the market new technologies regarding the battery are being developed and new problems to be solved, one of them the battery management system because each type of cell requires a specific way of handling. This research is done using the active research method to find out the actual problem on this subject and features a BMS should have, understand how they work and how to develop them applied to the purpose on this work. Once the features the BMS should have are clarified, it’s possible to develop a BMS for an electric racing car. The decisions are made taking into consideration the nature of the vehicle being developed. After the project done it’s clear to see that what was developed was not only the BMS itself but all the other factors around it, such as CAN communication, safety control, diagnostics and so on.

Reuse of electric vehicle battery in uninterruptible power supply

Tässä diplomityössä tarkasteltiin Nissan Leaf -sähköauton käytetyn litiumakun soveltuvuutta UPS-varavirtalaitteen energialähteeksi. Kun akku on heikentynyt niin ettei sen kapasiteetti enää ole riittävä autokäyttöön, sitä voidaan kuitenkin vielä hyödyntää muissa sovelluksissa, kuten UPS-laitteessa. Työ sai alkunsa osana GreenDataNet-projektia, jossa pyritään kehittämään datakeskuksiin ympäristöä vähemmän kuormittavia ratkaisuja käyttämällä uusiutuvia energialähteitä, akkujen uusiokäytöllä, sekä energianhallinnan optimoinnilla. Työssä käytiin läpi akun ja sen ohjausjärjestelmän ominaisuuksia, kerrottiin UPS:in ohjelmistoon tehdyistä muutoksista sekä esitettiin testitulokset. Lopputuloksena todettiin akun sopivan muuten hyvin UPS-käyttöön, mutta vaadittu päivittäinen kennojännitteiden tasaus ja sen aiheuttama katkos energian saatavuuteen heikentää UPSin käyttövarmuutta kuorman suojauksessa. Lopussa esitettiin muutamia ehdotuksia tämän ongelman korjaamiseksi.

STUDY OF HYBRID ELECTRIC VEHICLE BATTERY MODELING AND CONTROL USING AUTONOMIE

This report presents the research results of battery modeling and control for hybrid electric vehicles (HEV). The simulation study is conducted using plug-and-play powertrain and vehicle development software, Autonomie. The base vehicle model used for testing the performance of battery model and battery control strategy is the Prius MY04, a power-split hybrid electric vehicle model in Autonomie. To evaluate the battery performance for HEV applications, the Prius MY04 model and its powertrain energy flow in various vehicle operating modes are analyzed. The power outputs of the major powertrain components under different driving cycles are discussed with a focus on battery performance. The simulation results show that the vehicle fuel economy calculated by the Autonomie Prius MY04 model does not match very well with the official data provided by the department of energy (DOE). It is also found that the original battery model does not consider the impact of environmental temperature on battery cell capacities. To improve battery model, this study includes battery current loss on coulomb coefficient and the impact of environmental temperature on battery cell capacity in the model. In addition, voltage losses on both double layer effect and diffusion effect are included in the new battery model. The simulation results with new battery model show the reduced fuel economy error to the DOE data comparing with the original Autonomie Prius MY04 model.

Enabling long journeys in electric vehicles:design and demonstration of an infrastructure location model

This research develops a methodology and model formulation which suggests locations for rapid chargers to help assist infrastructure development and enable greater battery electric vehicle (BEV) usage. The model considers the likely travel patterns of BEVs and their subsequent charging demands across a large road network, where no prior candidate site information is required. Using a GIS-based methodology, polygons are constructed which represent the charging demand zones for particular routes across a real-world road network. The use of polygons allows the maximum number of charging combinations to be considered whilst limiting the input intensity needed for the model. Further polygons are added to represent deviation possibilities, meaning that placement of charge points away from the shortest path is possible, given a penalty function. A validation of the model is carried out by assessing the expected demand at current rapid charging locations and comparing to recorded empirical usage data. Results suggest that the developed model provides a good approximation to real world observations, and that for the provision of charging, location matters. The model is also implemented where no prior candidate site information is required. As such, locations are chosen based on the weighted overlay between several different routes where BEV journeys may be expected. In doing so many locations, or types of locations, could be compared against one another and then analysed in relation to siting practicalities, such as cost, land permission and infrastructure availability. Results show that efficient facility location, given numerous siting possibilities across a large road network can be achieved. Slight improvements to the standard greedy adding technique are made by adding combination weightings which aim to reward important long distance routes that require more than one charge to complete.

Development of a Predictive Control Function for a Plug-in Hybrid Electric Vehicle with Electrically-heated Catalyst

This master thesis work is focused on the development of a predictive EHC control function for a diesel plug-in hybrid electric vehicle equipped with a EURO 7 compliant exhaust aftertreatment system (EATS), with the purpose of showing the advantages provided by the implementation of a predictive control strategy with respect to a rule-based one. A preliminary step will be the definition of an accurate powertrain and EATS physical model, starting from already existing and validated applications. Then, a rule-based control strategy managing the torque split between the electric motor (EM) and the internal combustion engine (ICE) will be developed and calibrated, with the main target of limiting tailpipe NOx emission by taking into account EM and ICE operating conditions together with EATS conversion efficiency. The information available from vehicle connectivity will be used to reconstruct the future driving scenario, also referred to as electronic horizon (eHorizon), and in particular to predict ICE first start. Based on this knowledge, an EATS pre-heating phase can be planned to avoid low pollutant conversion efficiencies, thus preventing high NOx emission due to engine cold start. Consequently, the final NOx emission over the complete driving cycle will be strongly reduced, allowing to comply with the limits potentially set by the incoming EURO 7 regulation. Moreover, given the same NOx emission target, the gain achieved thanks to the implementation of an EHC predictive control function will allow to consider a simplified EATS layout, thus reducing the related manufacturing cost. The promising results achieved in terms of NOx emission reduction show the effectiveness of the application of a predictive control strategy focused on EATS thermal management and highlight the potential of a complete integration and parallel development of involved vehicle physical systems, control software and connectivity data management.

PCM-based battery thermal management systems, energy saving materials and LCA strategy for automotive

This PhD work arises from the necessity to give a contribution to the energy saving field, regarding automotive applications. The aim was to produce a multidisciplinary work to show how much important is to consider different aspects of an electric car realization: from innovative materials to cutting-edge battery thermal management systems (BTMSs), also dealing with the life cycle assessment (LCA) of the battery packs (BPs). Regarding the materials, it has been chosen to focus on carbon fiber composites as their use allows realizing light products with great mechanical properties. Processes and methods to produce carbon fiber goods have been analysed with a special attention on the university solar car Emilia 4. The work proceeds dealing with the common BTMSs on the market (air-cooled, cooling plates, heat pipes) and then it deepens some of the most innovative systems such as the PCM-based BTMSs after a previous experimental campaign to characterize the PCMs. After that, a complex experimental campaign regarding the PCM-based BTMSs has been carried on, considering both uninsulated and insulated systems. About the first category the tested systems have been pure PCM-based and copper-foam-loaded-PCM-based BTMSs; the insulated tested systems have been pure PCM-based and copper-foam-loaded-PCM-based BTMSs and both of these systems equipped with a liquid cooling circuit. The choice of lighter building materials and the optimization of the BTMS are strategies which helps in reducing the energy consumption, considering both the energy required by the car to move and the BP state of health (SOH). Focusing on this last factor, a clear explanation regarding the importance of taking care about the SOH is given by the analysis of a BP production energy consumption. This is why a final dissertation about the life cycle assessment (LCA) of a BP unit has been presented in this thesis.

Intelligent electric vehicle heuristic for energy resource management using simulated annealing

The smart grid concept appears as a suitable solution to guarantee the power system operation in the new electricity paradigm with electricity markets and integration of large amounts of Distributed Energy Resources (DERs). Virtual Power Player (VPP) will have a significant importance in the management of a smart grid. In the context of this new paradigm, Electric Vehicles (EVs) rise as a good available resource to be used as a DER by a VPP. This paper presents the application of the Simulated Annealing (SA) technique to solve the Energy Resource Management (ERM) of a VPP. It is also presented a new heuristic approach to intelligently handle the charge and discharge of the EVs. This heuristic process is incorporated in the SA technique, in order to improve the results of the ERM. The case study shows the results of the ERM for a 33-bus distribution network with three different EVs penetration levels, i. e., with 1000, 2000 and 3000 EVs. The results of the proposed adaptation of the SA technique are compared with a previous SA version and a deterministic technique.

Simulated Annealing Approach Applied to the Energy Resource Management Considering Demand Response for Electric Vehicle

The aggregation and management of Distributed Energy Resources (DERs) by an Virtual Power Players (VPP) is an important task in a smart grid context. The Energy Resource Management (ERM) of theses DERs can become a hard and complex optimization problem. The large integration of several DERs, including Electric Vehicles (EVs), may lead to a scenario in which the VPP needs several hours to have a solution for the ERM problem. This is the reason why it is necessary to use metaheuristic methodologies to come up with a good solution with a reasonable amount of time. The presented paper proposes a Simulated Annealing (SA) approach to determine the ERM considering an intensive use of DERs, mainly EVs. In this paper, the possibility to apply Demand Response (DR) programs to the EVs is considered. Moreover, a trip reduce DR program is implemented. The SA methodology is tested on a 32-bus distribution network with 2000 EVs, and the SA results are compared with a deterministic technique and particle swarm optimization results.

On-board electric vehicle battery charger with enhanced V2H operation mode

This paper proposes an on-board Electric Vehicle (EV) battery charger with enhanced Vehicle-to-Home (V2H) operation mode. For such purpose was adapted an on-board bidirectional battery charger prototype to allow the Grid-to-Vehicle (G2V), Vehicle-to-Grid (V2G) and V2H operation modes. Along the paper are presented the hardware topology and the control algorithms of this battery charger. The idea underlying to this paper is the operation of the on-board bidirectional battery charger as an energy backup system when occurs a power outages. For detecting the power outage were compared two strategies, one based on the half-cycle rms calculation of the power grid voltage, and another in the determination of the rms value based in a Kalman filter. The experimental results were obtained considering the on-board EV battery charger under the G2V, V2G, and V2H operation modes. The results show that the power outage detection is faster using a Kalman filter, up to 90% than the other strategy. This also enables a faster transition between operation modes when a power outage occurs.

An MILP model for the plug-in electric vehicle charging coordination problem in electrical distribution systems

A new mixed-integer linear programming (MILP) model is proposed to represent the plug-in electric vehicles (PEVs) charging coordination problem in electrical distribution systems. The proposed model defines the optimal charging schedule for each division of the considered period of time that minimizes the total energy costs. Moreover, priority charging criteria is taken into account. The steady-state operation of the electrical distribution system, as well as the PEV batteries charging is mathematically represented; furthermore, constraints related to limits of voltage, current and power generation are included. The proposed mathematical model was applied in an electrical distribution system used in the specialized literature and the results show that the model can be used in the solution of the PEVs charging problem.

Model predictive control in thermal management of multiprocessor systems-on-chip

MultiProcessor Systems-on-Chip (MPSoC) are the core of nowadays and next generation computing platforms. Their relevance in the global market continuously increase, occupying an important role both in everydaylife products (e.g. smartphones, tablets, laptops, cars) and in strategical market sectors as aviation, defense, robotics, medicine. Despite of the incredible performance improvements in the recent years processors manufacturers have had to deal with issues, commonly called “Walls”, that have hindered the processors development. After the famous “Power Wall”, that limited the maximum frequency of a single core and marked the birth of the modern multiprocessors system-on-chip, the “Thermal Wall” and the “Utilization Wall” are the actual key limiter for performance improvements. The former concerns the damaging effects of the high temperature on the chip caused by the large power densities dissipation, whereas the second refers to the impossibility of fully exploiting the computing power of the processor due to the limitations on power and temperature budgets. In this thesis we faced these challenges by developing efficient and reliable solutions able to maximize performance while limiting the maximum temperature below a fixed critical threshold and saving energy. This has been possible by exploiting the Model Predictive Controller (MPC) paradigm that solves an optimization problem subject to constraints in order to find the optimal control decisions for the future interval. A fully-distributedMPC-based thermal controller with a far lower complexity respect to a centralized one has been developed. The control feasibility and interesting properties for the simplification of the control design has been proved by studying a partial differential equation thermal model. Finally, the controller has been efficiently included in more complex control schemes able to minimize energy consumption and deal with mixed-criticalities tasks

Dual Active Bridge based Battery Charger for Plug-in Hybrid Electric Vehicle with Charging Current Containing Low Frequency Ripple

High power density is strongly preferable for the on-board battery charger of Plug-in Hybrid Electric Vehicle (PHEV). Wide band gap devices, such as Gallium Nitride HEMTs are being explored to push to higher switching frequency and reduce passive component size. In this case, the bulk DC link capacitor of AC-DC Power Factor Correction (PFC) stage, which is usually necessary to store ripple power of two times the line frequency in a DC current charging system, becomes a major barrier on power density. If low frequency ripple is allowed in the battery, the DC link capacitance can be significantly reduced. This paper focuses on the operation of a battery charging system, which is comprised of one Full Bridge (FB) AC-DC stage and one Dual Active Bridge (DAB) DC-DC stage, with charging current containing low frequency ripple at two times line frequency, designated as sinusoidal charging. DAB operation under sinusoidal charging is investigated. Two types of control schemes are proposed and implemented in an experimental prototype. It is proved that closed loop current control is the better. Full system test including both FB AC-DC stage and DAB DC-DC stage verified the concept of sinusoidal charging, which may lead to potentially very high power density battery charger for PHEV.

Passenger Exposure to Magnetic Fields due to the Batteries of an Electric Vehicle

In electric vehicles, passengers sit very close to an electric system of significant power. The high currents achieved in these vehicles mean that the passengers could be exposed to significant magnetic fields. One of the electric devices present in the power train are the batteries. In this paper, a methodology to evaluate the magnetic field created by these batteries is presented. First, the magnetic field generated by a single battery is analyzed using finite elements simulations. Results are compared to laboratory measurements, taken from a real battery, in order to validate the model. After this, the magnetic field created by a complete battery pack is estimated and results are discussed.

In situ diagnostics and prognostics of solder fatigue in IGBT modules for electric vehicle drives

This paper proposes an in situ diagnostic and prognostic (D&P) technology to monitor the health condition of insulated gate bipolar transistors (IGBTs) used in EVs with a focus on the IGBTs' solder layer fatigue. IGBTs' thermal impedance and the junction temperature can be used as health indicators for through-life condition monitoring (CM) where the terminal characteristics are measured and the devices' internal temperature-sensitive parameters are employed as temperature sensors to estimate the junction temperature. An auxiliary power supply unit, which can be converted from the battery's 12-V dc supply, provides power to the in situ test circuits and CM data can be stored in the on-board data-logger for further offline analysis. The proposed method is experimentally validated on the developed test circuitry and also compared with finite-element thermoelectrical simulation. The test results from thermal cycling are also compared with acoustic microscope and thermal images. The developed circuitry is proved to be effective to detect solder fatigue while each IGBT in the converter can be examined sequentially during red-light stopping or services. The D&P circuitry can utilize existing on-board hardware and be embedded in the IGBT's gate drive unit.

Electric Vehicle Battery Charger: Wireless Power Transfer System Controlled by Magnetic Core Reactor

This paper presents a control process and frequency adjustment based on the magnetic core reactor for electric vehicle battery charger. Since few decades ago, there have been significant developments in technologies used in wireless power transfer systems, namely in battery charger. In the wireless power transfer systems is essential that the frequency of the primary circuit be equal to the frequency of the secondary circuit so there is the maximum energy transfer. The magnetic core reactor allows controlling the frequencies on both sides of the transmission and reception circuits. Also, the assembly diagrams and test results are presented.