Battery Management Systems (BMS) perform different operations for better use of energy stored in lithium-ion batteries (LiBs). The LiBs are a non -line ar
Request PDF | Constrained generalized predictive control of battery charging process based on a coupled thermoelectric model | Battery temperature is a primary factor affecting the battery ...
One of the most challenging barriers to this technology is its operating temperature range which is limited within 15°C–35°C. This review aims to provide a …
Abstract. Performance, safety, and longevity of batteries are all strongly impacted by thermal management, which is an essential component of battery design and operation. This work examines how accurate temperature control can result in significant improvements in performance and reliability with a focus on battery thermal heating. Predicting …
The active battery thermal management system is critical for the security of electric vehicles. In this article, a novel battery thermal management system and the control …
Thermal control simulations are conducted under regular operating and extreme operating conditions, and two controllers are applied to control battery temperature with proper intervals which is conducive to enhance the battery charge-discharge efficiency. The results indicate that, for any operating condition, the fuzzy logic controller shows excellence in terms of …
Battery charging control Model predictive control Electrothermal model State-of-charge estimation abstract Lithium-ion battery charging management has become an enabling technology towards a paradigm shift of electrified mobility. Fast charging is desired for convenience improvements but may excessively degrade battery''s health or even cause …
4.2 Predictive Battery Thermal Management for Maximum Regenerative Braking. The purpose of the predictive battery thermal management is to use the maximum regenerative braking energy in the on-zone delivery phase of the CEP usage. To achieve this, the battery has to be conditioned particularly under cold ambient conditions. The battery ...
Keywords: hybrid electric air-ground vehicle; energy management strategy; battery temperature; model predictive control; Pontryagin''s minimum principle 1. Introduction It is acknowledged that the existing traditional vehicles present challenges in contexts of traffic congestion and complex working conditions, such as bridge cutoff, mountain range, and fire …
This study introduces a novel hybrid system that combines a machine learning-based battery temperature prediction model with an online battery parameter identification unit. The identification unit continuously …
The driving range is reduced 30.9% when battery temperature drops from 20 °C to −10 °C [9]. Meanwhile, during charging and regenerative braking, the low-temperature environment leads to a great risk of lithium plating, which causes a loss of lithium and affects battery lifetime [10], [11]. Therefore, it is important to heat LIBs to ensure normal and safe …
6 · Zhuang et al. [19] combine the optimization of the battery pack structure with the cooling strategy, equip the battery pack with hollow perturbation prism parameters to improve the temperature uniformity, and employ an intelligent cooling method based on fuzzy model predictive control to adjust the cooling intensity according to the heat dissipation demand and …
For the engine–battery CTMS under low-temperature conditions, the temperature control requirements of the engine and power battery include rapid warm-up (RWP) and temperature maintenance (TM). In the RWP stage, the temperatures of the engine and power battery are much lower than the expected temperature. The engine needs to be …
To maximize the vehicle driving range, the means of controlling the battery temperature should minimize the energy consumption. In this paper, stochastic model predictive control is applied to the battery-cooling controller. Effective model predictive control requires a good but simple system model with proper estimation of near-future ...
In this paper, we developed a quick temperature prediction algorithm based on a thermal convolution method (TCM) to calculate the core temperature of a flat heat pipe-based battery thermal management system (FHP-BTMS) under …
DOI: 10.1016/j.apenergy.2020.115232 Corpus ID: 219934598; Actively temperature controlled health-aware fast charging method for lithium-ion battery using nonlinear model predictive control
To forecast battery temperature and to control thermal performance, researchers are increasingly using machine and deep learning approaches. Existing literature indicates that among these techniques, ANN particularly LSTM, GRU, NARX, and FFNN, offer advantages in battery temperature prediction and thermal management. The advantage of …
Use EIS to quickly and effectively predict the internal temperature changes of LIBs. No hardware temperature sensors and thermal model are required. The methods to predict battery temperature based on impedance, phase shift, …
modulate battery pack temperature through refrigeration cycles or heat pumps, while passive systems harness high thermal conductivity materials for heat dissipation. Hybrid systems, combining both approaches, aspire for optimal temperature control. Various cooling techniques, including liquid and air cooling, are also scrutinized.
MPC evaluated at with í µí± = 2 using 14s6p battery configuration, no thermal limitations; (a) is the state of charge; (b) is the battery surface temperature; (c) is the EM torque; (d) is the ...
Predictive Control (MPC) strategy for battery thermal and en-ergy management of electric vehicle (EV), aiming at improving fuel economy through real-time prediction and optimization. In the first layer, the long-term traffic flow information and an approximate model reflective of the relatively slow battery temperature dynamics are leveraged to minimize energy con-sumption …
Abstract: In order to keep a lithium-ion battery within optimal temperature range for excellent performance and long lifespan, it is necessary to have an effective control strategy for a battery thermal management system (BTMS) consisting of electric pump, cooling plate and radiator. In this paper, a control-oriented model for BTMS is established, and an …
Institute of Automation and Control, Graz University of Technology, Inffeldgasse 21/B/I, 8010, Graz, Austria. S. Koch, M. Steinberger & M. Horn . Lam Research AG, SEZ-Straße 1, 9500, Villach, Austria. M. Ponikvar. Authors. S. Koch. View author publications. You can also search for this author in PubMed Google Scholar. M. Ponikvar. View author …
As the temperature has a great effect on the cycle life and capacity of power battery on electric vehicles (EVs), a practical battery thermal management (BTM) strategy is required to adjust the battery temperature within an appropriate range and reduce the temperature inconsistency in the battery module. To achieve the multiple objectives, a …
This paper reviews the existing control methods used to control charging and discharging processes, focusing on their impacts on battery life. Classical and modern methods are studied together in ...
A real-time nonlinear model predictive control (NMPC) method for the thermal management of a plug-in hybrid electric vehicle was presented to keep the Li-ion battery within …
Electric vehicle (EV) is developed because of its environmental friendliness, energy-saving and high efficiency. For improving the performance of the energy storage system of EV, this paper proposes an energy management strategy (EMS) based model predictive control (MPC) for the battery/supercapacitor hybrid energy storage system (HESS), which takes …
In this paper, a model predictive control (MPC) method with a fast-balancing strategy is proposed to address the inconsistency issue of individual cell in lithium-ion battery packs. Firstly, an optimal energy transfer direction is investigated to improve equalization efficiency and reduce energy loss. Then, a MPC-based equalization algorithm is developed to …
This research studies the control of electro-thermal dynamics of cylindrical Li-ion battery packs in electric vehicles (EVs). These dynamics are coupled by the charging-discharging current which generates the Joule heating that directly affect to the operation of battery cells. Hence, to guarantee the battery cells'' temperatures in a desired range for their …
In order to keep the lithium-ion battery within the optimal temperature range to achieve excellent battery performance and extend its lifespan, it is necessary to have an effective control ...
Shuts down battery if temperatures exceed critical levels. EVs, aerospace, critical systems [100] User Interaction and Notifications: Driver Alerts: Notifies the driver if the battery temperature is unsafe. EVs, consumer electronics [101] Adaptive Control: Learning Algorithms: Adapt strategies over time based on past scenarios. EVs, smart ...
Description: This paper explores the role of Internet of Things (IoT) technology in revolutionizing battery management systems (BMS) for electric vehicles (EVs). It examines how IoT enables real-time monitoring, data analytics, and remote control capabilities in BMS, leading to improved battery performance, predictive
Predictive Battery Thermal Management using Quantile Convolutional Neural Networks. Andreas M. Billert, Stefan Erschen, +1 author. F. Gauterin. Published in Transport …
The predictive cooling strategy is based on a model predictive control (MPC) formulation to maintain the battery temperature in its optimal range (to increase efficiency) and avoid high ...
Abstract: Battery temperature is a primary factor affecting the battery performance. Suitable battery temperature control, in particular internal temperature control can not only guarantee the battery operation safety but also improve its efficiency. This is however challenging as existing controller designs for battery charging
The proposed control method shows significantly reduced energy consumption while keeping acceptable temperature regulation performance compared to a typical temperature controller, such as a thermostat-type controller. The performance and safety of a battery for electric vehicles get worse when the battery temperature is very low or very high.
way the battery temperature is controlled should use as little energy as possible. In this project, the battery controller is cooled with the help of a probabilistic model prediction controller. Model predictive control works best when you have a good, easy model of the system and a good way to predict what will happen in the near future. Part of the cooling system of the battery is …
Fig. 2 shows a typical block diagram of the functions and algorithms of BMS. As shown in the figure, the BMS is mainly used to collect data (voltage, current, temperature, etc.) from the battery pack. On the one hand, these data are used to estimate the states of the battery on short time scales, for example direct ampere–hour integration for SOC estimation, or model …
@article{Amini2020CabinAB, title={Cabin and Battery Thermal Management of Connected and Automated HEVs for Improved Energy Efficiency Using Hierarchical Model Predictive Control}, author={Mohammad Reza Amini and Hao Wang and Xun Gong and Dominic Liao-McPherson and Ilya V. Kolmanovsky and Jing Sun}, journal={IEEE Transactions …
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