A virtual sound provision apparatus for an electric vehicle includes a driving information detector configured to detect vehicle driving information for outputting a virtual driving sound, a microphone configured to detect an actual driving sound generated from the electric vehicle, a controller configured to determine a characteristic of a target sound based on an acceleration and deceleration driving pattern of a driver from an accelerator pedal input value and a brake pedal input value of the driver, and generating and outputting a sound control signal for outputting the virtual driving sound having the characteristic of the target sound based on the determined characteristic information of the target sound and characteristic information of the actual driving sound, and a sound device configured to output a virtual engine sound that simulates an engine sound from the electric vehicle at the time of acceleration and deceleration according to the sound control signal.

An electrified vehicle includes a motor, a clutch, a transmission, a rotational speed sensor configured to detect a rotational speed of the motor, and a control circuit configured to control the motor. The control circuit performs: a learning process of detecting a change in the rotational speed of the motor by the rotational speed sensor when the shift change is performed; and a control process of controlling the rotational speed of the motor based on the change in the rotational speed detected in the learning process, when the shift change is performed after the learning process.

A method for determining MTPA, flux-weakening, and MTPV operating points over the full speed range of an IPM motor for the most efficient torque control of the motor using a neural network is provided. The neural network is trained using a cloud-based neural network training algorithm. A special technique is developed to generate neural network training data, that is particularly suitable and favorable, to develop a high-performance neural network-based IPM torque control system, and the impact of variable motor parameters is embedded into the neural network system development and training. The provided method can achieve a fast and accurate current reference generation with a simple neural network structure, for optimal torque control of an IPM motor. The method can handle the MTPA, MTPV, and flux-weakening operation considering physical motor constraints.

A hybrid vehicle includes an engine, a first motor generator, a dynamic damper, and a power split mechanism. The dynamic damper includes an output-side rotating member, a spring element, and a second motor generator connected to the output-side rotating member so as to transmit the power. The dynamic damper is configured by connecting the output-side rotating member and the second motor generator via the spring element. The power split mechanism splits a power from the engine to the first motor generator and to the output-side rotating member. The control device includes an electronic control unit. The electronic control unit configured to change execution modes of rattling noise suppression control based on a spring characteristic of the dynamic damper. The rattling noise suppression control is a control to suppress rattling noise resulting from rotational fluctuations of the engine.

A slip control device for an electric vehicle which accurately determines slippage occurrence with only a rotation angle sensor for motor rotation control and perform rapid control to eliminate the slippage, is provided. A threshold calculation module (21) calculates a normal angular acceleration of a motor depending on a manipulation amount of an accelerator to obtain a threshold, and an angular acceleration calculator (22) differentiates a detection value from a rotation angle sensor (3a) twice to calculate an angular acceleration. A slip determination (23) determines whether a drive wheel (7) has slipped, and a torque limitation (25) limits a torque when a slippage has occurred. The determination (23) determines the angular acceleration and a threshold. The determination (23) counts a number of consecutive times it is determined that the threshold is exceeded, and determines that a slippage has occurred, if the number of consecutive times has reached a set value. The limitation (25) limits a torque developed by a motor unit for a drive wheel laterally opposite to the drive wheel determined as having slipped.

A method for active vibration control of a hybrid electric vehicle may include: selecting a reference angle signal based on position information of a motor or an engine; generating a reference angle based on information of the reference angle signal; setting up a period of fast Fourier transform (FFT) and analyzing the FFT signal; setting up a reference spectrum according to an engine speed and an engine load; extracting a vibration component from each frequency based on information of the reference spectrum; selecting and adding a removal object frequency from the vibration of each frequency and performing inverse FFT; determining a basic amplitude ratio according to the engine speed and the engine load and an adjustable rate according to the engine load; and performing active vibration control of each frequency based on the information of the basic amplitude ratio, the adjustable rate, and the engine torque.

An unsprung state detection part (140) calculates a variation amount X (=||), which is a magnitude of a difference between a detected angle output from a resolver rotational angle sensor (40) for detecting a rotational angle of an in-wheel motor (30) and an estimated angle of a motor rotational angle (S11 to S13). The estimated angle can be calculated by adding an estimated angle of the rotation of the motor (30) in one calculation cycle to a detected angle n1 of the previous calculation cycle. When the variation amount X is more than a road surface determination threshold Xref, the unsprung state detection part (140) determines that the travel road on which a vehicle (1) is traveling is a rough road (S14, S15). As a result, the road surface determination can be made by using the rotational angle sensor (40).

A hybrid operation machine of which an electric motor is driven by at least one among a power generator driven by an engine and an energy storage system for storing regenerative energy, and comprising: a motor drive for driving the electric motor; an acceleration sensor for sensing an accelerator pedal command; and a control unit for mapping the accelerator pedal command to a speed command during a low speed traveling operation and controlling a traveling unit through the motor drive, wherein the control unit controls the acceleration and deceleration of the electric motor according to the mapped speed command and generates regenerative energy according to the deceleration of the electric motor.

A method for learning a touch point of an engine clutch of a hybrid electric vehicle including a motor connected to a transmission and an engine selectively connected to the motor through the engine clutch includes determining whether a learning condition of the touch point of the engine clutch is satisfied, releasing a transmission clutch and controlling a motor speed when the learning condition is satisfied, increasing a coupling pressure of the engine clutch when a change amount of the motor speed is less than a first predetermined value, comparing a change amount of a motor torque according to the increased coupling pressure of the engine clutch with a second predetermined value, and learning the touch point of the engine clutch when the change amount of the motor torque is greater than or equal to the second predetermined value.

A drive control system for an electric motor includes a slippage determination device, a tentative vibration damper torque calculator, a vibration damper torque limit value setting device, a vibration damper torque setting device, and a control device. The vibration damper torque setting device is configured to set a control torque obtained by limiting a tentative vibration damper torque using a limit value set by the vibration damper torque limit value setting device. The control device is configured to control driving of the electric motor in accordance with a command value of a torque obtained by combining a requested torque for the electric motor with the control torque set by the vibration damper torque setting device.