Browse Topic: Battery thermal management
Thermal Management System (TMS) for Battery Electric Vehicles (BEV) incorporates maintaining optimum temperature for cabin, battery and e-powertrain subsystems under different charging and discharging conditions at various ambient temperatures. Current methods of thermal management are inefficient, complex and lead to wastage of energy and battery capacity loss due to inability of energy transfer between subsystems. In this paper, the energy consumption of an electric vehicle's thermal management system is reduced by a novel approach for integration of various subsystems. Integrated Thermal Management System (ITMS) integrates air conditioning system, battery thermal management and e-powertrain system. Characteristics of existing integration strategies are studied, compared, and classified based on their energy efficiency for different operating conditions. A new integrated system is proposed with a heat pump system for cabin and waste heat recovery from e-powertrain. Various cooling
Modern battery management systems, as part of Battery Digital Twin, include cloud-based predictive analytics algorithms. These algorithms predicts critical parameters like Thermal runaway events, state of health (SOH), state of charge (SOC), remaining useful life (RUL), etc. However, relying only on cloud-based computations adds significant latency to time-sensitive procedures such as thermal runaway monitoring. This is a very critical and safety function and delay is not acceptable, but automobiles operate in various areas throughout the intended path of travel, internet connectivity varies, resulting in a delay in data delivery to the cloud and similarly delay in return of the detected warning to the driver back in the vehicle. As a result, the inherent lag in data transfer between the cloud and vehicles challenges the present deployment of cloud-based real-time monitoring solutions. This study proposes application of Federated Learning and applying to a thermal runaway model in low
Charging a battery electric vehicle at extreme temperatures can lead to battery deterioration without proper thermal management. To avoid battery degradation, charging current is generally limited at extreme hot and cold battery temperatures. Splitting the wall power between charging and the thermal management system with the aim of minimizing charging time is a challenging problem especially with the strong thermal coupling with the charging current. Existing research focus on formulating the battery thermal management control problem as a minimum charging time optimal control problem. Such control strategy force the driver to charge with minimum time and higher charging cost irrespective of their driving schedule. This paper presents a driver-centric DCFC control framework by formulating the power split between thermal management and charging as an optimal control problem with the goal of improving the wall-to-vehicle energy efficiency. Proposed energy-efficient charging strategy
Items per page:
50
1 – 50 of 224