Energy Storage Systems for Electric Vehicles

The global electric car fleet exceeded 7 million battery electric vehicles and plug-in hybrid electric vehicles in 2019, and will continue to increase in the future, as electrification is an important means of decreasing the greenhouse gas emissions of the transportation sector. The energy storage s...

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Year of Publication:2020
Language:English
Physical Description:1 electronic resource (550 p.)
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520 |a The global electric car fleet exceeded 7 million battery electric vehicles and plug-in hybrid electric vehicles in 2019, and will continue to increase in the future, as electrification is an important means of decreasing the greenhouse gas emissions of the transportation sector. The energy storage system is a very central component of the electric vehicle. The storage system needs to be cost-competitive, light, efficient, safe, and reliable, and to occupy little space and last for a long time. It should also be produced and disposed of in an environmentally friendly manner. This leaves many research challenges, and the purpose of this book is therefore to provide a platform for sharing the latest findings on energy storage systems for electric vehicles (electric cars, buses, aircraft, ships, etc.) Research in energy storage systems requires several sciences working together, and this book therefore include contributions from many different disciplines; this covers a wide range of topics, e.g. battery-management systems, state-of-charge and state-of-health estimation, thermal-battery-management systems, power electronics for energy storage devices, battery aging modelling, battery reuse and recycling, etc. 
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653 |a non-aqueous electrolyte 
653 |a nitrile-based solvents 
653 |a butyronitrile 
653 |a SEI forming additives 
653 |a fast charging 
653 |a power batteries 
653 |a improved second-order RC equivalent circuit 
653 |a fuzzy unscented Kalman filtering algorithm 
653 |a joint estimation 
653 |a electric bus 
653 |a battery 
653 |a energy efficiency 
653 |a environmental conditions 
653 |a hybrid electric vehicles (HEVs) 
653 |a battery life 
653 |a multi-objective energy management 
653 |a adaptive equivalent consumption minimization strategy (A-ECMS) 
653 |a pontryagin’s minimum principle (PMP) 
653 |a particle swarm optimization (PSO) 
653 |a recurrent-neural-network (RNN) 
653 |a fuel cell hybrid electric vehicle 
653 |a least squares support vector machines (LSSVM) 
653 |a driving conditions identification 
653 |a power distribution 
653 |a electric vehicle 
653 |a lithium-ion battery 
653 |a estimation 
653 |a Kalman filter 
653 |a state-of-charge 
653 |a state-of-health 
653 |a resistance 
653 |a open-circuit voltage 
653 |a battery capacity 
653 |a battery modelling and simulation 
653 |a battery testing cycler 
653 |a battery thermal model 
653 |a lithium-ion polymer battery 
653 |a SLI battery 
653 |a dual-motor energy recovery 
653 |a regenerative braking system 
653 |a CVT speed ratio control 
653 |a motor minimum loss 
653 |a energy consumption and efficiency characteristics 
653 |a braking force distribution 
653 |a oil–electric–hydraulic hybrid system 
653 |a lowest instantaneous energy costs 
653 |a energy management 
653 |a global optimization 
653 |a retired batteries 
653 |a energy storage applications 
653 |a layered bidirectional equalization 
653 |a equalization algorithm 
653 |a state of charge 
653 |a available capacity 
653 |a adaptive model-based algorithm 
653 |a square root cubature Kalman filter 
653 |a li-ion battery 
653 |a performance degradation modelling 
653 |a electrified propulsion 
653 |a battery sizing 
653 |a powertrain optimization 
653 |a optimal energy management 
653 |a heat and mass transfer 
653 |a thermal analysis 
653 |a Lithium-ion battery 
653 |a micro-channel cooling plate 
653 |a battery thermal management 
653 |a MeshWorks 
653 |a CFD 
653 |a diffusion induced stress 
653 |a hydrostatic stress influence on diffusion 
653 |a electrode particle model 
653 |a battery mechanical aging 
653 |a coulomb counting 
653 |a open circuit voltage 
653 |a state of health 
653 |a temperature 
653 |a new energy vehicle 
653 |a power battery 
653 |a battery reusing 
653 |a echelon utilization 
653 |a battery recycling 
653 |a electric vehicles 
653 |a electro-hydraulic braking 
653 |a braking intention 
653 |a mode switching 
653 |a torque coordinated control 
653 |a Electric Truck Simulator 
653 |a Electric Vehicle (EV) 
653 |a Vehicle Routing Problem (VRP) 
653 |a Traveling Salesman Problem (TSP) 
653 |a least-energy routing algorithm 
653 |a EV batteries 
653 |a metric evaluation 
653 |a AC–AC converters 
653 |a battery chargers 
653 |a power conversion harmonics 
653 |a wireless power transmission 
653 |a electrochemical–thermal model 
653 |a artificial intelligence 
653 |a artificial neural networks 
653 |a hybrid vehicles 
653 |a state-of-charge estimation (SOC) 
653 |a linear quadratic estimator 
653 |a lithium ion battery 
653 |a iron phosphate 
653 |a cell expansion 
653 |a force 
653 |a lithium-ion cobalt battery 
653 |a state of energy 
653 |a adaptive EKF SOC estimation 
653 |a linear observer SOC estimation 
653 |a MATLAB 
653 |a Simscape 
653 |a electric buses 
653 |a thermal energy storage 
653 |a latent heat storage 
653 |a metallic phase change material 
653 |a cabin heating 
653 |a fuel cell 
653 |a automated guided vehicle 
653 |a hybrid energy storage system 
653 |a model-based design 
653 |a waveforms modeling 
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