Examples described herein provide a computer-implemented method that includes calculating, by a processing device, a motor acceleration error based at least in part on a motor torque and a motor speed. The method further includes calculating, by the processing device, a regression fit line based at least in part on the motor acceleration error. The method further includes identifying, by the processing device, a zero point using the regression fit line. The method further includes comparing, by the processing device, the zero point to a datum reference to determine a difference. The method further includes integrating, by the processing device, the difference to determine the lash angle. The method further includes controlling, by the processing device, the motor based at least in part on the lash angle.

Examples described herein provide a computer-implemented method that includes calculating, by a processing device, a motor acceleration error based at least in part on a motor torque and a motor speed. The method further includes calculating, by the processing device, a regression fit line based at least in part on the motor acceleration error. The method further includes identifying, by the processing device, a zero point using the regression fit line. The method further includes comparing, by the processing device, the zero point to a datum reference to determine a difference. The method further includes integrating, by the processing device, the difference to determine the lash angle. The method further includes controlling, by the processing device, the motor based at least in part on the lash angle.

A method controls the current output of a battery for driving a rail vehicle. A battery actual current I.sub.bat,ist passes via a converter to an asynchronous motor, being a drive for the vehicle. The battery actual current I.sub.bat,ist is set by control circuits as a function of a feedforward control torque M.sub.ff and a specified torque M.sub.tf. The feedforward control torque M.sub.ff is calculated using a transfer function H.sub.sys(z), which maps the torque setpoint value M.sub.soll onto the battery actual current I.sub.bat,ist as follows: I.sub.bat(z) H.sub.sys(z) M.sub.soll(z). Accordingly, a zero-point z=znmp, which lies outside the unit circle, is determined by the transfer function H.sub.sys(z). The feedforward control torque M.sub.ff is calculated as follows: M.sub.ff(z) I.sub.bat,neu(z)/(H.sub.sys(z) z) where: I.sub.bat,neu(z)=I.sub.bat,ideal(z) I.sub.bat,ideal(z=znmp) where: I.sub.bat,neu[n]=I.sub.bat,ideal[n] for all n>0, so that pole point/zero point cancellation is reached by z=znmp at the battery ideal current.

The method includes: when the vehicle satisfies a one-pedal activating condition, controlling the vehicle to enter a one-pedal-function activating mode; when the vehicle enters the one-pedal-function activating mode and satisfies a parking-controlling-function activating condition, acquiring current-vehicle-speed information, road-slope information and a first electric-motor recovering torque; based on the current-vehicle-speed information and the road-slope information, calculating to obtain a parking torque; acquiring a first torque difference between the parking torque and the first electric-motor recovering torque; and performing pressure buildup to the vehicle based on the first torque difference, to control the vehicle to complete a parking operation.

Tow bar arrangement (100) for interconnection of a pulling vehicle (10) and a pulled trailer (20). The arrangement (100) comprises a control device (110) with a force sensor (111) arranged to sense an instantaneous relative force between vehicle (10) and trailer (20). The control device (110) is arranged to produce a control signal for an electric motor (21) arranged to propel the trailer (20) so that a motor force counter-acts said measured force. The invention is characterised in that the control device (110) is arranged to a first time series of force measurements, in that the control device (110) comprises a low-pass filter (112) producing a second low-pass filtered time series, and in that a regulator (113) is ar-ranged to regulate said second time series to produce said control signal.

A method for determining an optimized torque distribution to the wheels of a road vehicle comprising the steps of determining a table of distribution of the torque between a front axle and a rear axle; determining a second table and a third table of distribution of the torque between a right wheel and a left wheel of the rear axle and of the front axle, respectively; detecting the current longitudinal dynamics; using the first, the second and the third table to determine a current value of the first, of the second and of the third distribution factor, respectively, based on the current longitudinal speed and on the current longitudinal acceleration of the road vehicle.

Informed towing is provided. Towing information is identified, by a towing vehicle, with respect to a towed vehicle to be towed by the towing vehicle. A towed configuration of the towed vehicle is monitored. Responsive to the towed configuration of the towed vehicle being incorrect according to the towing information, a warning is displayed in the HMI indicating the incorrect towing configuration.

Informed towing is provided. Towing information is identified, by a towing vehicle, with respect to a towed vehicle to be towed by the towing vehicle. A towed configuration of the towed vehicle is monitored. Responsive to the towed configuration of the towed vehicle being incorrect according to the towing information, a warning is displayed in the HMI indicating the incorrect towing configuration.

An autonomous robotic vehicle is capable of detecting, identifying, and locating the source of gas leaks such as methane. Because of the number of operating components within the vehicle, it may also be considered a robotic system. The robotic vehicle can be remotely operated or can move autonomously within a jobsite. The vehicle selectively deploys a source detection device that precisely locates the source of a leak. The vehicle relays data to stakeholders and remains powered that enables operation of the vehicle over an extended period. Monitoring and control of the vehicle is enabled through a software interface viewable to a user on a mobile communications device or personal computer.

An autonomous robotic vehicle is capable of detecting, identifying, and locating the source of gas leaks such as methane. Because of the number of operating components within the vehicle, it may also be considered a robotic system. The robotic vehicle can be remotely operated or can move autonomously within a jobsite. The vehicle selectively deploys a source detection device that precisely locates the source of a leak. The vehicle relays data to stakeholders and remains powered that enables operation of the vehicle over an extended period. Monitoring and control of the vehicle is enabled through a software interface viewable to a user on a mobile communications device or personal computer.