2975 results about "Hybrid vehicle" patented technology

To enable detection of temperature rise of electronic equipment disposed in a battery pack due to radiation heat in an exhaust passage.SOLUTION: A battery pack 50 disposed on the underfloor of a hybrid vehicle 1 includes: a battery stuck 55 where battery cells are laminated; a battery ECU51 and a monitoring unit 52. A temperature sensor 53 fitted to a flue gas passage 94 is disposed at a position between the battery ECU51 and the monitoring unit 52, and an exhaust pipe 21. The temperature sensor 53 is disposed between the battery ECU51 and the monitoring unit 52, and the exhaust pipe 21, and therefore favorably detects the temperature rise of the battery ECU 51 and the monitoring unit 52 due to radiation heat from the exhaust pipe 21.SELECTED DRAWING: Figure 2

The present disclosure describes a vehicle charging system comprising a vehicle charging gun comprising at least two pins, a protective earth (PE) pin configured to connect to ground and a proximity pilot (PP) pin configured to detect when the vehicle charging gun has been inserted into a vehicle; and an apparatus to couple with the vehicle charging gun, the apparatus comprising: a switch operable between a first position and a second position, the switch being controlled by a controller, wherein, when the switch is in the first position, the switch enables the vehicle or a vehicle charging station to detect that the vehicle charging gun is inserted into a vehicle inlet port of the vehicle, and when the switch is in the second position, the apparatus generates an electrical effect that simulates the removal of the vehicle charging gun from the vehicle inlet port.

The invention relates to the technical field of new energy vehicles, in particular to a multi-working-condition energy management method and system for a hybrid chariot, and the method comprises the steps: determining a corresponding working condition weight coefficient through obtaining the altitude, environment temperature and road condition data in real time, and the real-time working parameters of three power sources, namely an engine, a fuel cell and a lithium battery, so as to achieve the multi-working-condition energy management of the hybrid chariot; the system constructs a multi-objective optimization model based on the data to realize comprehensive fuel consumption minimization, lithium battery SOC balance and lithium battery life protection, and the model comprises establishment of a power source efficiency parameter mapping relation, determination of a corresponding relation between lithium battery power and cycle life, and construction of a membership function of an optimization objective. By adopting a method of combining Pareto local optimization and fuzzy evaluation, the optimal power distribution proportion among the engine, the fuel cell and the lithium battery is calculated, the overall efficiency of the hybrid chariot is effectively improved, and the service life of the hybrid chariot is effectively prolonged.

The invention provides a hybrid vehicle energy management method, device and equipment and a medium, and the method comprises the steps: obtaining the real-time traffic information and configuration information of a vehicle, and calculating the demand power and demand torque of the vehicle according to the real-time traffic information and configuration information; calculating energy consumption of the battery according to the battery remaining capacity, the capacity information and the temperature information to obtain energy consumption information of the battery; power parameters of the vehicle are obtained, and the actual power and the actual torque of the vehicle are calculated according to the energy consumption information and the power parameters; actual energy consumption of the vehicle is calculated according to the actual power and the actual torque, and an energy distribution strategy is made according to the actual energy consumption; and constructing a dynamic programming algorithm to perform power distribution on an engine and a motor of the vehicle according to the energy distribution strategy. According to the technical scheme of the embodiment, through real-time interaction of the Internet of Vehicles, the vehicle can complete efficient energy distribution according to the processing information, and energy consumption and environmental pollution of the hybrid power vehicle are reduced.

The invention provides a path collaborative planning method for a hybrid vehicle group conflict area, and belongs to the technical field of vehicle path planning. According to the method, the virtual following target point of the driver is obtained by sampling the speed of the manual driving vehicle and the deviation path distance relative to the road reference line to generate the sampling track, and the driving behavior of the driver in the unstructured road environment is predicted; a forward deduction method of vehicle dynamics is combined to predict a short-time trajectory of the manually driven vehicle as a reference trajectory to evaluate the confidence coefficient of the reference trajectory, so that the accuracy of the sampling trajectory can be improved, and the collaboration and safety among the vehicles are improved; besides, in combination with information of the space-time risk field, the priority and the driving track of the unmanned vehicle are dynamically adjusted by adopting a space-time hybrid A star algorithm based on a dynamic risk field, so that efficient dynamic redistribution of space-time resources in a conflict area scene is realized, and the collision risk of the vehicle in the conflict area is reduced. According to the method, the multi-vehicle cooperative operation stability in the mixed scene can be remarkably improved.

The invention relates to an energy management method and system for a hybrid electric vehicle, and the method comprises the steps: obtaining the actual driving condition data of a target vehicle under a current energy distribution strategy; based on the actual driving condition data, dynamically optimizing a first student model deployed in the target vehicle to obtain a second student model; the first student model is obtained by performing knowledge distillation based on a pre-trained teacher model; and processing the real-time sensor data of the target vehicle through the second student model to obtain a latest energy distribution strategy of the target vehicle, and controlling the target vehicle according to the latest energy distribution strategy. Through the method and the device, the problem of poor vehicle energy efficiency performance caused by lack of dynamic adaptation capability for complex working conditions in an actual driving scene is solved, online continuous learning and performance iterative optimization of the model are realized, and the working condition adaptation capability and generalization capability of the model are enhanced, so that the complex working conditions in the driving scene are dynamically adapted, and the vehicle energy efficiency is improved. And the vehicle energy efficiency performance is optimized.

The invention discloses a method and a system for testing and evaluating energy consumption of a hybrid power system in a plateau road environment, is used for testing and evaluating energy consumption of a hybrid power system vehicle, and relates to the technical field of energy consumption testing of hybrid power vehicles. Dividing the plateau road into a plurality of working condition segments according to driving working conditions, and recording road features of each working condition segment; obtaining driving behavior characteristics of a driver in each working condition segment, and combining the driving behavior characteristics with the corresponding working condition segments to form a plateau working condition segment pool; and extracting vehicle data corresponding to each driving behavior working condition fragment, and calculating vehicle energy consumption of each driving behavior working condition fragment according to the vehicle data, thereby completing vehicle energy consumption test evaluation.

The invention discloses a hydrogen fuel cell hybrid electric vehicle energy management method based on robust optimization, and the method comprises the following steps: building a vehicle model: building a longitudinal dynamic model of a hydrogen fuel cell hybrid electric vehicle, determining a vehicle demand power model, and building an evaluation function of instantaneous hydrogen consumption, constructing an output power model of the hydrogen fuel cell and the capacitor; performing uncertainty analysis on the hydrogen fuel cell hybrid electric vehicle, determining uncertain parameters in the vehicle model, and constructing an uncertainty set of the uncertain parameters; the method comprises the following steps: constructing an sLSTM vehicle speed prediction model through vehicle historical speed data, predicting a future driving speed, analyzing the uncertainty of the prediction model, and outputting a prediction speed error in a current prediction time domain; and according to the optimization target, constructing a target function for minimizing the hydrogen consumption, solving the target function by applying a robust optimization algorithm, and outputting a first control result of the optimal control sequence.

The invention relates to the technical field of automobile charging, and particularly discloses a vehicle circuit system with a reverse charging function, comprising a main battery pack; the bidirectional inverter is electrically connected to the main battery pack and is configured to convert external alternating current into direct current to charge the main battery pack in a charging mode and convert the direct current of the main battery pack into alternating current to be output in a discharging mode; the charging control module is connected to the output end of the bidirectional inverter and used for processing input / output electric energy of different specifications; the multifunctional output interface comprises at least one alternating current interface and a direct current interface; and the system control unit, the integrated current detection module, the temperature monitoring module and the fault diagnosis module are respectively in communication connection with the bidirectional inverter, the charging control module and the output interface through a CAN bus. The vehicle power battery can reversely supply power to external equipment or other vehicles, meanwhile, the conventional charging function and the energy recycling function are compatible, and the method is suitable for new energy vehicles, hybrid electric vehicles and other scenes.

The invention relates to a state of charge correction method and device, electronic equipment and a storage medium. The charge state correction method comprises the following steps: acquiring battery state data, dynamic characteristic parameters and vehicle state data of a battery in the hybrid electric vehicle within a first preset time period; determining whether the battery is in a polarization state according to the dynamic characteristic parameters; if the battery is in the polarization state, whether the current whole vehicle condition meets the active correction condition of the charge state or not is determined according to the vehicle state data and the battery state data; and if the current whole vehicle condition meets the active correction condition of the charge state, the current charge state of the battery is actively corrected to be the target charge state. According to the embodiment of the invention, the method can improve the estimation accuracy of the state of charge of the battery, is suitable for the special scenes that the engine of the hybrid electric vehicle works frequently and the fixed-rate charge-discharge interval is very few, reduces the energy management misjudgment caused by the SOC error, prolongs the service life of the battery, and improves the overall stability of the system.

The present disclosures relate to methods and systems for a hybrid powertrain. The hybrid powertrain system includes an integrated axle configured to provide mechanical power to a first pair of wheels, the integrated axle comprising a first motor-generator and a first drive axle such that the first motor-generator and at least a portion of the first drive axle are mechanically coupled to a common housing. The system also includes a second motor-generator configured to be mechanically coupled with an engine via a first clutch and mechanically coupled with a second drive axle via a second clutch, the second drive axle mechanically coupled with a second pair of wheels. A controller is electrically coupled with the first and second motor-generators, the engine, and the first and second clutches, the controller configured to enable a fully electric mode, a series hybrid mode, a parallel hybrid mode, and a regenerative mode of operation.

Aspects of the present invention relate to a method and to a control system for controlling an electric traction motor of a vehicle, the control system comprising one or more controllers, wherein the control system is configured to: limit a rate of change of torque requested from the electric traction motor for changing speed towards a speed target, in dependence on a lash crossing protection rate limiter; and upon removal of the limit prior to the speed reaching the speed target, inhibit initial increase of a torque requested from the electric traction motor for changing speed towards the speed target.

Provided is a vehicle control device 21 capable of automatically starting electric traveling with high quietness in a case where a hybrid vehicle approaches a base without a driver performing a switching operation or setting a destination with respect to a navigation device when the hybrid vehicle travels near the base. The vehicle control device 21 is mounted on a vehicle 100 which switches between a first traveling state in which the vehicle 100 is driven by transmitting a driving force of an electric motor 107 by power supply from a battery 105 to drive wheels 109 and a second traveling state in which the vehicle 100 is driven with at least operation of an engine 102. The vehicle control device 21 includes a determination value storage unit 27 which allocates and stores, for each of a plurality of predetermined points, a determination value obtained based on a battery consumption amount required for the vehicle 100 to travel in the first traveling state from a predetermined point to the bases 31, 31A, and 31B and a target battery remaining amount at the time of arrival at the bases 31, 31A, and 31B, and a traveling state determination unit 28 which starts traveling in the first traveling state in a case where a current battery charge amount of the vehicle 100 exceeds a determination value corresponding to a current point of the vehicle 100.

An AI-connected-electrified (ACE) heavy truck system equipped with an intelligent multi-mode hybrid (iMMH) powertrain system and a vehicle supervision control strategy based on machine learning (ML) or reinforcement learning (RL) paradigm are presented. This system ensures industry-leading power and braking performance of the ACE heavy truck while automatically optimizes both energy saving and emission reduction based on the vehicle's dynamic driving data and 3D electronic map information of roads for any transport event. In this application, the conventional analog electronic control (AEC) method is replaced by a novel digital pulse control (DPC) method on the instantaneous power function of the engine. The DPC method converts the complex surface working conditions of the AEC engine of the hybrid vehicles into simpler pre-defined working condition lines of the DPC engine. Consequently, the multi-variable nonlinear technical problem of simultaneously optimizing real driving environment (RDE) fuel consumption and pollutant emissions of the ACE heavy truck is simplified into two decoupled quasi-liner optimization problems, and ensures the reduction of on-vehicle computing resources for real-time AI inference computation and the improvement of the optimal performance, the convergent rate, and the robustness of the corresponding fuel-saving algorithm for the trained ML model or the learned RL model. Ultimately, the ACE truck achieves in the engineering sense the global minimum RDE fuel consumption and pollutant emissions meeting the standard consistently at high performance to cost ratio for any transport event and the RDE fuel consumption is decoupled from the vehicle configuration parameters and the human driver.

A system for determining a secondary axle torque of a hybrid vehicle is disclosed. The hybrid vehicle includes a primary axle driven by an engine and a secondary axle driven by an electric motor. The system includes one or more sensors configured to detect a driver torque request, and a control module in communication with the one or more sensors. The control module is configured to receive data from the one or more sensors indicative of the driver torque request, calculate a primary torque target for the primary axle based on an optimal engine torque, calculate a secondary torque target for the secondary axle based on the calculated primary torque target and the driver torque request, and generate a secondary torque command to drive the secondary axle based on the calculated secondary torque target and the driver torque request. Other example systems and methods are also disclosed.

The invention discloses a hybrid power vehicle energy and heat collaborative optimization control system and method, which comprehensively considers the influence of heat effects generated by different engine and battery power distribution obtained by an energy management strategy decision on a heat management system. And the influence of the thermal load change of the thermal management system on the whole vehicle energy management strategy formulation and the fuel economy caused by the change of the load of the thermal management actuator can be avoided, so that the whole vehicle economy of the hybrid power vehicle can be improved; the stability of the charge state of the battery system is ensured; the energy utilization rate and the engine system performance are effectively improved; according to the method, the heat-energy coupling mechanism and energy consumption characteristics of the plug-in hybrid power vehicle are analyzed, it is ensured that all the function modules are located in the optimal temperature working condition interval in different driving modes, and therefore the performance and safety of power system components are effectively considered, the interaction influence of heat management and energy management in a traditional strategy is improved, and the system reliability is improved. And the fuel economy of the whole vehicle is improved.

The invention provides a hybrid vehicle energy management system and method based on a traffic state, a storage medium and a computer program product, and the system comprises the steps: constructing a congestion prediction model based on a deep learning model, the congestion prediction is used for predicting the traffic flow and the driving speed of a future time period according to the historical traffic flow data and the historical driving speed data; calculating a first congestion index according to the predicted traffic flow in the future period; calculating a second congestion index according to the predicted driving vehicle speed sequence of the future time period; performing weighted calculation on the first congestion index and the second congestion index to obtain a comprehensive traffic congestion index in a future time period; traffic jam types are divided according to the interval where the comprehensive traffic jam index is located; and determining an energy management mode and / or a target SOC of the hybrid vehicle based on the traffic jam type. According to the invention, multi-source data are collected and analyzed in real time, congestion is accurately quantified by using a deep learning algorithm, an energy distribution strategy of vehicles is dynamically adjusted, and the energy utilization efficiency is improved.

The invention discloses a plug-in hybrid electric vehicle thermal management system and a control method thereof, and belongs to the technical field of new energy vehicle thermal management. The whole system is divided into four cooling loops according to heat exchange gradient requirements of different parts; the three loops are respectively a high-temperature cooling and air-conditioning heating system loop, a low-temperature cooling system loop, a power battery heating / cooling system loop and an air-conditioning refrigerating system loop, and through the coupling design of the different system loops, the energy consumption is reduced, the cruising ability of the hybrid electric vehicle is improved, and the service life of the hybrid electric vehicle is prolonged. Therefore, safe and reliable operation of a power system, a battery system and an air-conditioning system under various modes / working conditions is guaranteed, functional requirements of cooling, heating, refrigerating and the like of the whole vehicle can be met, all parts can be guaranteed to work within a reasonable temperature range, and the thermal management system is simple and comprehensive in design, saves energy consumption and is suitable for popularization and application. And the cruising ability of the hybrid electric vehicle can be effectively improved.

The invention relates to the technical field of battery management of hybrid power vehicles, in particular to a hybrid power semitrailer battery management system and a multi-mode balance control method, and the hybrid power semitrailer battery management system comprises a data acquisition module, a main control module, a balance execution module, a thermal management module, a communication interface module and a safety protection module. Accurate battery state estimation and dynamic parameter updating are realized through an advanced algorithm and a model, a decision basis is provided for equalization and thermal management, an active and passive hybrid architecture and an intelligent topology switching strategy are adopted, energy management between battery cells is efficiently realized, energy waste is avoided, wind speed and wind direction are dynamically regulated and controlled by applying reinforcement learning, and energy consumption is reduced. The temperature consistency of the battery cell is maintained with low energy consumption, the energy utilization efficiency, the state control precision and the operation safety of the battery management system are remarkably improved, the service life of the battery is effectively prolonged, and stable operation of the system is guaranteed.

The invention discloses a self-adaptive hybrid power energy management method based on demand power prediction, and belongs to the field of hybrid electric vehicle energy management, and the method comprises the steps: 1, based on the historical information of a fixed route and the positioning information of a navigation system, utilizing an improved LSTM (Long-Short-Term Memory) to carry out power demand prediction on the basis of the historical information of the fixed route and the positioning information of the navigation system; carrying out certain time domain prediction on the vehicle speed and the required power of the fixed commuting vehicle through an LSTM (Long Short Term Memory) algorithm; 2, establishing an energy consumption minimum solving problem in a short time domain by estimating a required power range of a certain time domain, and solving an optimal basic equivalent factor sequence by using a particle swarm algorithm of adaptive weight; 3, equivalent factors under different required powers are corrected by considering the SOC and the temperature of the battery, an equivalent factor correction MAP is constructed through offline simulation and real vehicle calibration, and the equivalent factors are adjusted online in real time; 4, after the determined equivalent factors are obtained, an ECMS strategy is executed to determine the optimal output torque of the engine and the optimal output torque of the motor; according to the invention, the energy management control is close to global optimum, and the economic performance and working condition adaptability of the vehicle can be improved.

Provided is a power transmission apparatus for a hybrid vehicle, the power transmission apparatus including a connecting shaft having an edge portion connected to a mass by a connecting plate, the connecting shaft being coupled to an outer side of a first rotor shaft connected to a first rotor of a first motor, and a drive plate positioned adjacent to a crankshaft while facing the connecting shaft, the drive plate being configured to connect the mass and the crankshaft.

A travel control device for a hybrid vehicle includes: an acceleration control part for controlling a traveling motor generator or an engine based on a depression amount of an accelerator pedal; and a regenerative control part for controlling the traveling motor generator with a regenerative control intensity set by an operation part. The acceleration control part includes: an EV priority control portion for prioritizing EV traveling over engine traveling. The regenerative control part includes: a restriction portion for restricting or prohibiting regenerative braking; and a forced regeneration portion for performing regenerative braking on a driving wheel and rotationally driving a power generation motor generator by electricity generated in the traveling motor generator to rotationally drive an engine, if the regenerative braking intensity is increased by the operation part in a state where the restriction portion restricts or prohibits the regenerative braking. The acceleration control part deselects an EV priority mode if the regenerative braking intensity is increased by the operation part in a state where the EV priority mode is selected and acceptance of electricity to the driving battery is restricted.

A combined piston ring used for a new energy hybrid power automobile engine belongs to the technical field of engines and comprises a ring body inner plate in contact with the inner side face of a main body mechanism, an ash discharge groove formed in the ring body inner plate, a scraping plate installed in a groove formed in the ring body inner plate and a plurality of shaking reeds evenly distributed between the two ring bodies. The scraping plate is in contact with the inner wall of a groove formed in the piston; in the working process of an engine, residual carbon deposits on the inner wall of a groove formed in a piston are scraped off in the rotating process of a scraping plate, the carbon deposits enter an ash discharging groove along an inclined face arranged on the scraping plate, a connecting plate makes contact with a shaking reed in the rotating process so that the shaking reed can be intermittently compressed and bounced off, the carbon deposits in the shaking reed can be prevented from being accumulated into blocks, and the service life of the connecting plate is prolonged. The carbon deposition can be effectively prevented from being accumulated in a gap between the piston ring and the piston, the piston ring is blocked, and the work of the piston is influenced.

The invention discloses a hybrid power vehicle collaborative thermal management method and system based on energy flow intelligent perception. The method comprises the following steps: sensing and predicting multi-dimensional energy flow characteristics of an engine in real time through a pre-trained time sequence neural network model; the predicted value is used as a feedforward signal, real-time temperature feedback of the power battery is combined, and a thermal management cooperative control instruction is generated through feedforward-feedback cooperative decision logic; and finally, a heat exchange path between the engine cooling system and the battery heat management system and respective execution mechanisms are dynamically adjusted, so that prospective active cooperative temperature control is realized. The problems of passive response, control delay and low energy efficiency of an existing thermal management system are solved, and accurate and efficient two-way optimization management of the thermal states of the engine and the battery is achieved.

The invention discloses a real-time SLMP fuel cell hybrid electric vehicle energy management method. The method comprises the following steps: firstly, collecting vehicle operation data in real time, constructing an operation state vector containing kinetic parameters, and initializing a state transition matrix as agent action input; on the basis, the speed and the acceleration are predicted through a self-learning Markov predictor, and dynamic self-adaptive power distribution of the fuel cell and the power cell is achieved in combination with a multi-objective optimization function and power distribution constraints. The method passes hardware-in-the-loop (HIL) verification, aims at reducing hydrogen consumption and improving efficiency, and exits if two times of circulation are not passed. Compared with a traditional method based on rules or static optimization, the method innovatively embeds a self-learning mechanism, has the advantages of being high in adaptability, high in prediction precision and good in generalization performance, and is suitable for energy management optimization under complex working conditions.

Described is a hybrid transportation system with hybrid vehicles (H-vehicles) that can travel on pavement (or off-road), then transition to railroad track travel, and then later transition back onto pavement without stopping or requiring an operator to exit the vehicle. At static rail junctions (with no moving switch parts) the H-vehicle selects its outgoing track. Turns at passive junctions are made by applying lateral force which may be applied using multiple methods including side roller diverters and steering. Separate road wheels and rail wheels may be employed on an H-vehicle, or a combination wheel can be used with concentric road and rail wheel components. Combination wheels may be locked together or unlocked with relative rotational angular velocities. Transition between road and rail travel is facilitated using transition spans which connect roads to rails. Improved rail-only vehicles (R-) vehicles and junctions are also described.

The invention particularly discloses a plug-in hybrid power whole vehicle refrigeration control method and system. The method comprises the steps that a corresponding relation table of temperature difference values and compressor rotating speeds is set; the difference value between the actual temperature of the battery water inlet and the target temperature of the battery water inlet is obtained, and the battery refrigeration required rotating speed is calculated through the parameters obtained by looking up the corresponding relation table; the difference value between the actual temperature of the evaporator and the target temperature of the evaporator is obtained, and the refrigeration required rotating speed of the passenger compartment is calculated through parameters obtained by looking up the corresponding relation table; and the sum of the battery refrigeration required rotating speed and the passenger compartment refrigeration required rotating speed serves as the rotating speed of a compressor, and speed regulation control over the compressor is conducted. Accurate control over the refrigerating capacity can be improved, and the refrigerating effect is enhanced.

The invention discloses a control method, device and equipment of a hybrid electric vehicle and a storage medium, and relates to the technical field of hybrid electric vehicles, and the control method comprises the steps that the current driving mode, the current SOC, the current vehicle speed, the whole vehicle demand power and environment information of the vehicle are obtained; determining a vehicle state according to the environment information, the current driving mode and the current SOC; a range extender starting strategy is determined according to the vehicle state, and a range extender of the vehicle is controlled; when an engine of the range extender is started, determining a target operation mode and power generation power of the range extender according to the current vehicle speed and the required power of the whole vehicle; and determining the power generation rotating speed of the range extender according to the environment information and the power generation power of the range extender, and controlling the engine. The technical problems of low energy management efficiency and unstable operation caused by the fact that fixed threshold value control cannot adapt to environmental changes are solved, accurate matching of range extender start-stop control and power generation strategies under complex environmental conditions is achieved, and the energy utilization efficiency and the operation stability of the whole vehicle are improved.

Methods and systems are provided for selectively controlling hybrid drive modes of a hybrid vehicle to reduce emissions. In one example, a method may include using route planning and vehicle operating conditions to identify emissions reducing opportunities. In one example, in response to a route distance not exceeding an electric range, the method includes suppressing an operation of an engine based on the route data, ambient temperature, and cabin pre-conditioning. In response to the route distance exceeding the electric range, further in anticipation of a fuel station along the route, where the fuel station has a fuel with a carbon footprint less than a low carbon threshold, the method includes operating the hybrid vehicle in a charge sustaining or charge increasing mode prior to a refueling event at the fuel station.

Disclosed is an energy storage system, in particular for use in a vehicle, preferably for use in a hybrid vehicle, wherein the energy storage system has the following: a multiplicity of lithium ion cells, a housing with an interior space for receiving the lithium-ion cells and having an opening and a cover device. A barrier layer is provided, at least in certain areas, between the interior of the housing and the inner faces of the housing which bound the interior. In this context, the cover device can be or is connected to the housing in such a way that the opening of the housing is or can be closed, specifically in such a way that the cover device forms, at least in certain areas, an outer face of the housing which is closed in this way. The cover device is preferably embodied as a cooling device for regulating the temperature of the energy storage system.